System and method for tracking and alerting for vehicle speeds

ABSTRACT

A computer system and method for storing and processing GPS data for a plurality of vehicles to provide speed reports and alerts for fleets of vehicles, including alerts for speed data. The system and method can provide, for a graphic user interface, an alert when an operational metric for a vehicle meets or exceeds at least one predetermined criterion established for the operational metric, wherein the operational metric includes a speed metric.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application No.61/553,518, filed Oct. 31, 2011, the entirety of which is incorporatedherein by reference.

DESCRIPTION OF RELATED ART

It is known to provide an on-board unit which uses technology such asGPS (Global Positioning System) to monitor a vehicle's positions andtransmit wireless uploads to a central host system as well as manage ofincoming data traffic without data losses or corruption and/or withoutdatabase record locking. Such a unit may also upload vehicle statusevents such as engine fault events. GB2345824 and U.S. Pat. No.7,388,518 describes such systems and methods therefor, the entirety ofeach of which are incorporated by reference herein.

SUMMARY

A computer system including at least one computer processor and computerreadable storage medium or media including computer code and at leastone storage device in which is stored GPS data for a plurality ofvehicles the system comprising: a memory including GPS event databaseincluding GPS event data transmitted from a plurality of GPS devices,each GPS device associated with a vehicle, and stored over a period oftime; and one or more processors programmed at least to receive GPSevent data transmitted from a plurality of GPS devices, each GPS deviceassociated a vehicle; store in a memory operatively coupled to at leastone of the processors, the GPS event data; analyze the GPS event data toderive a plurality of operational metrics for each vehicle; provide, fora graphic user interface, an interactive display configured display agraphic representation of at least one operational metric for each of aplurality of vehicles, including a representation including arepresentation of a speed limit event, wherein the system is operativelyconnected to at least one speed database including speed data.

A method comprising, in at least one computer and a computer readablestorage medium or media including computer code: receiving GPS eventdata transmitted from a plurality of GPS devices, each GPS deviceassociated a vehicle; storing, for each vehicle, in a memory operativelycoupled to at least one of the processors, the GPS event data; analyzingthe GPS event data to derive a plurality of operational metrics for eachvehicle; and providing, for a graphic user interface, an interactivedisplay configured display a graphic presentation of at least oneoperational metric for each of a plurality of vehicles, including arepresentation including a representation of a speed limit event,wherein the system is operatively connected to at least one speeddatabase including speed data.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated in the figures of the accompanying drawings,which are meant to be exemplary and not limiting, and in which likereferences are intended to refer to like or corresponding things.

FIGS. 1A-1D are block diagrams of a representative computer system.

FIG. 2 depicts a representative GPS system.

FIGS. 3A-3T depict exemplary representations for graphic userinterfaces.

FIG. 4 is a flowchart depicting exemplary processes.

FIGS. 5A-B depict a graph and table for determining a Standard Deviationfrom mean for vehicle inclusion.

FIGS. 6A-6C show an exemplary flow showing GPS event data analysis.

FIG. 7 depicts a table including activation identifications for industrysegments and geographical areas.

FIG. 8 depicts a flow for fleet benchmarking.

FIGS. 9A-C depicts an exemplary display representations for mappingintegration

FIG. 10 depicts an exemplary display representation for a sequence ofground level representations of a route.

DETAILED DESCRIPTION OF THE EMBODIMENTS

It is to be understood that the figures and descriptions of the presentinvention have been simplified to illustrate elements that are relevantfor a clear understanding of the present invention, while eliminating,for purposes of clarity, many other elements which are conventional inthis art. Those of ordinary skill in the art will, recognize that otherelements are desirable for implementing the present invention. However,because such elements are well known in the art, and because they do notfacilitate a better understanding of the present invention, a discussionof such elements is not provided herein.

The use of the terms “a,” “an,” “at least one,” “one or more,” andsimilar terms indicate one of a feature or element as well as more thanone of a feature. The use of the term “the” to refer to the feature doesnot imply only one of the feature and element.

When an ordinal number (such as “first,” “second,” “third,” and so on)is used as an adjective before a term, that ordinal number is used(unless expressly or clearly specified otherwise) merely to indicate aparticular feature, such as to distinguish that particular feature fromanother feature that is described by the same term or by a similar term.

When a single device, article or other product is described herein, morethan one device/article (whether or not they cooperate) mayalternatively be used in place of the single device/article that isdescribed. Accordingly, the functionality that is described as beingpossessed by a device may alternatively be possessed by more than onedevice/article (whether or not they cooperate). Similarly, where morethan one device, article or other product is described herein (whetheror not they cooperate), a single device/article may alternatively beused in place of the more than one device or article that is described.Accordingly, the various functionality that is described as beingpossessed by more than one device or article may alternatively bepossessed by a single device/article.

The functionality and/or the features of a single device that isdescribed may be alternatively embodied by one or more other deviceswhich are described but are not explicitly described as having suchfunctionality/features. Thus, other embodiments need not include thedescribed device itself, but rather can include the one or more otherdevices which would, in those other embodiments, have suchfunctionality/features.

The present invention will now be described in detail on the basis ofexemplary embodiments. The invention disclosed herein may be practicedusing programmable digital computers and networks therefor.

As shown in FIGS. 1A-1B, disclosed is a system 100, which includes acomputer 140 containing a processor 145, memory 157 and other componentstypically present in general purpose computers.

FIG. 1A is a block diagram of a representative computer. The computersystem 140 includes at least one processor 145, such as an Intel Core™or Xeon™ series microprocessor or a Freescale™ PowerPC™ microprocessor,coupled to a communications channel 147. The computer system 140 furtherincludes an input device 149 such as, e.g., a keyboard or mouse, anoutput device 151 such as, e.g., a CRT or LCD display, a communicationsinterface 153, a data storage device 155 such as a magnetic disk or anoptical disk, and memory 157 such as Random-Access Memory (RAM), eachcoupled to the communications channel 147. The communications interface153 may be coupled to a network such as the Internet.

Memory 157 stores information accessible by processor 145, includinginstructions that may be executed by the processor 145. It also includesdata that may be retrieved, manipulated or stored by the processor. Thememory may be of any type capable of storing information accessible bythe processor, such as a hard-drive, memory card, ROM, RAM, DVD, CD-ROM,write-capable, and read-only memories. The processor 145 may be anywell-known processor, such as processors from Intel Corporation or AMD.Alternatively, the processor may be a dedicated controller such as anASIC.

The instructions may be any set of instructions to be executed directly(such as machine code) or indirectly (such as scripts) by the processor.In that regard, the terms “instructions,” “steps” and “programs” may beused interchangeably herein. The instructions may be stored in objectcode format for direct processing by the processor, or in any othercomputer language including scripts or collections of independent sourcecode modules that are interpreted on demand or compiled in advance.Functions, methods and routines of the instructions are explained inmore detail below.

One skilled in the art will recognize that, although the data storagedevice 155 and memory 157 are depicted as different units, the datastorage device 155 and memory 157 can be parts of the same unit orunits, and that the functions of one can be shared in whole or in partby the other, e.g., as RAM disks, virtual memory, etc. It will also beappreciated that any particular computer may have multiple components ofa given type, e.g., processors 145, input devices 149, communicationsinterfaces 153, etc.

The data storage device 155 and/or memory 157 may store an operatingsystem 160 such as Microsoft Windows 7®, Windows XP® or Vista™, Linux®,Mac OS®, or Unix®. Other programs 162 may be stored instead of or inaddition to the operating system. It will be appreciated that a computersystem may also be implemented on platforms and operating systems otherthan those mentioned. Any operating system 160 or other program 162, orany part of either, may be written using one or more programminglanguages such as, e.g., Java®, C, C++, C#, Visual Basic®, VB.NET®,Perl, Ruby, Python, or other programming languages, possibly usingobject oriented design and/or coding techniques.

Data may be retrieved, stored or modified by processor 145 in accordancewith the instructions. For instance, although the system and method isnot limited by any particular data structure, the data may be stored incomputer registers, in a relational database as a table having aplurality of different fields and records, XML documents, or flat files.The data may also be formatted in any computer-readable format such as,but not limited to, binary values, ASCII or Unicode. By further way ofexample only, image data may be stored as bitmaps comprised of pixelsthat are stored in compressed or uncompressed, or lossless or lossyformats (e.g., JPEG), vector-based formats (e.g., SVG) or computerinstructions for drawing graphics. Moreover, the data may comprise anyinformation sufficient to identify the relevant information, such asnumbers, descriptive text, proprietary codes, pointers, references todata stored in other memories (including other network locations) orinformation that is used by a function to calculate the relevant data.

It will be understood by those of ordinary skill in the art that theprocessor and memory may actually comprise multiple processors andmemories that may or may not be stored within the same physical housing.For example, some of the instructions and data may be stored onremovable CD-ROM and others within a read-only computer chip. Some orall of the instructions and data may be stored in a location physicallyremote from, yet still accessible by, the processor. Similarly, theprocessor may actually comprise a collection of processors which may ormay not operate in parallel.

One skilled in the art will recognize that the computer system 140 mayalso include additional components and/or systems, such as networkconnections, additional memory, additional processors, networkinterfaces, input/output busses, for example. One skilled in the artwill also recognize that the programs and data may be received by andstored in the system in alternative ways. For example, acomputer-readable storage medium (CRSM) reader 164, such as, e.g., amagnetic disk drive, magneto-optical drive, optical disk drive, or flashdrive, may be coupled to the communications bus 147 for reading from acomputer-readable storage medium (CRSM) 166 such as, e.g., a magneticdisk, a magneto-optical disk, an optical disk, or flash RAM.Accordingly, the computer system 140 may receive programs and/or datavia the CRSM reader 164. Further, it will be appreciated that the term“memory” herein is intended to include various types of suitable datastorage media, whether permanent or temporary, including among otherthings the data storage device 155, the memory 157, and the CSRM 166.

Two or more computer systems 140 may be connected, e.g., in one or morenetworks, via, e.g., their respective communications interfaces 155and/or network interfaces (not depicted).

A computer system network is shown in FIG. 113. A network 182 may, forexample, connect one or more workstations 184 with each other and withother computer systems, such as file servers 186 or mail servers 188.The connection may be achieved tangibly, e.g., via Ethernet® or opticalcables, or wirelessly, e.g., through use of modulated microwave signalsaccording to the IEEE 802.11 family of standards. A computer system thatparticipates in the network may send data to another computer system inthe network via the network connection.

One use of a network 180 is to enable a computer system to provideservices to other computer systems, consume services provided by othercomputer systems, or both. For example, a file server 186 may providecommon storage of files for one or more of the workstations 190 on anetwork 182. A workstation 190 sends data including a request for a fileto the file server 186 via the network 182 and the file server 186 mayrespond by sending the data from the file back to the requestingworkstation 190.

As will be recognized by those skilled in the relevant art, the terms“workstation,” “client,” and “server” are used herein to describe acomputer's function in a particular context. A workstation may, forexample, be a computer that one or more users work with directly, e.g.,through a keyboard and monitor directly coupled to the computer system.A computer system that requests a service through a network is oftenreferred to as a client, and a computer system that provides a serviceis often referred to as a server. But any particular workstation may beindistinguishable in its hardware, configuration, operating system,and/or other software from a client, server, or both.

In one aspect, computer 204 is a server communicating with one or moreclient computers 184,192. For example, computer 204 may be a web serveror a hub and data storage service. Each client computer may beconfigured similarly to the server 184, 192, with a processor, memoryand instructions 240. Each client computer 184, 192 may be a personalcomputer, intended for use by a person, having all the internalcomponents normally found in a personal computer such as a centralprocessing unit (CPU), display device 151 (for example, a monitor havinga screen, a projector, a touch-screen, a small LCD screen, a television,or another device such as an electrical device that is operable todisplay information processed by the processor), CD-ROM, hard-drive,user input 149 (for example, a mouse, keyboard, touch-screen ormicrophone), speakers, modem and/or network interface device (telephone,cable or otherwise) and all of the components used for connecting theseelements to one another. Moreover, computers in accordance with thesystems and methods described herein may comprise any device capable ofprocessing instructions and transmitting data to and from humans andother computers including general purpose computers, PDAs, networkcomputers lacking local storage capability, and set-top boxes fortelevisions.

Although the client computers 184, 192 may comprise a full-sizedpersonal computer, the system and method may also be used in connectionwith mobile devices capable of wirelessly exchanging data with a serverover a network such as the Internet. For example, client computer1184,192 may be a wireless-enabled PDA such as an iPhone, and Androidenabled smart phone, a Blackberry phone, or another Internet-capablecellular phone. In either regard, the user may input information using asmall keyboard (in the case of a Blackberry phone), a keypad (in thecase of a typical cell phone), a touch screen (in the case of a PDAand/or smart phone) or any other means of user input.

Client computers 184, 192 may include a component, such as circuits, todetermine the geographic location of the device. For example, mobiledevice may include a GPS receiver. By way of further example, thecomponent may include software for determining the position of thedevice based on other signals received at the mobile device, such assignals received at a cell phone's antenna from one or more cell phonetowers if the mobile device is a cell phone.

Servers 186, 188, 202, 204 and client computers 184 and 192 are capableof direct and indirect communication, such as over a network 180, 200.Although only a few computers are depicted in FIGS. 1A-1B, it should beappreciated that a typical system can include a large number ofconnected computers, with each different computer being at a differentnode of the network 200. The network, and intervening nodes, maycomprise various configurations and protocols including the Internet,World Wide Web, intranets, virtual private networks, wide area networks,local networks, private networks using communication protocolsproprietary to one or more companies, Ethernet, WiFi and HTTP, andvarious combinations of the foregoing. Such communication may befacilitated by any device capable of transmitting data to and from othercomputers, such as modems (e.g., dial-up, cable or fiber optic) andwireless interfaces.

Although certain advantages are obtained when information is transmittedor received as noted above, other aspects of the system and method arenot limited to any particular manner of transmission of information. Forexample, in some aspects, information may be sent via a medium such as adisk, tape or CD-ROM. In other aspects, the information may betransmitted in a non-electronic format and manually entered into thesystem. Yet further, although some functions are indicated as takingplace on a server and others on a client, various aspects of the systemand method may be implemented by a single computer having a singleprocessor.

A network 182 may be connected to one or more other networks 180, e.g.,via a router 196. A router 196 may also act as a firewall, monitoringand/or restricting the flow of data to and/or from a network 180 asconfigured to protect the network. A firewall may alternatively be aseparate device (not pictured) from the router 196

A network of networks 180 may be referred to as an internet. The term“the Internet” 200 refers to the worldwide network of interconnected,packet-switched data networks that uses the Internet Protocol (IP) toroute and transfer data. A client and server on different networks maycommunicate via the Internet 200. For example, a workstation 190 mayrequest a World Wide Web document from a Web Server 202. The Web Server202 may process the request and pass it to, e.g., an Application Server204. The Application Server 204 may then conduct further processing,which may include, for example, sending data to and/or receiving datafrom one or more other data sources. Such a data source may include,e.g., other servers on the same network.

For example in one embodiment, an on-board GPS unit uploads information(eg. via a hub 153) about a vehicle v1, v2 . . . vn to a central hostsystem 208. Information about the vehicle derived from the GPSinformation can be presented to a user on a display device 151, forexample, as a layout shown in FIG. 2.

In one embodiment, the system is programmed at least to receive GPS evendata recorded by a GPS (Global Positioning System) device, for example,using an on-board unit which uses technology such as GPS to monitor avehicle's positions and transmit wireless uploads to a central hostsystem. Referring to FIG. 2 a vehicle tracking system comprises on-boardunits 1 in vehicles v1, v2, v3 . . . vn, which communicate wirelesslyvia mobile networks 2 to gateways 3. In this diagram two wirelessprotocols are indicated, namely GPRS and SMS. However there aretypically a variety of additional protocols. The gateways 3 communicateusing protocols such as UDP and TCP via the Internet 4 with a hostsystem 7 having receivers 5 which are operating system services, and adata storage system 6. The incoming data is written from the receivers 5to the data storage system 6, which includes a communication hub 153 anddatabase 208. GB2345824 and U.S. Pat. No. 7,388,518 describes suchsystems and methods therefor, the entirety of each of which areincorporated by reference herein.

FIG. 1C is a block diagram of a host system 7 showing an exemplarysystem configuration for a host system 7. As shown therein, acommunications layer 153 is operable to receive incoming GPS data andwrite data from the receivers 5 to the data storage system 208. The datastorage system can be divided into any number of databases and logicallayers for data analysis and storage. For example, a messaging layer 208b can be configured to store GPS event data from GPS on-board units 1 ina GPS event database 211. A separated routing database 212 could beprovided to store mapping and route data based on, inter alia, GPS datato store routes traveled by vehicles. Another database layer 208 a caninclude a business logic database 204 and a reporting database 210 tostore rules for analysis of data and reports analyzed data respectively.

A database layer 208 b can be operably connected to other databases, forexample external databases 204. For example the system can beoperatively connected to at least one speed database including speeddata or traffic data. For instance, one or more speed databases caninclude speed data comprising, for example, a record of a posted speedlimit for a route and/or a record of an average traffic/road speed for aroute.

For example, an external database 204 can provide traffic data whichshows congestion along routes to be traveled by a vehicle, which can beused in conjunction with GPS data 211 and business logic 204 to reroutevehicles or create reports as to congested routes. An applications layer204, such as an application sever 204, can be used to run applicationsprocessing, which may include, for example, sending data to and/orreceiving data from one or more other data sources such as clientworkstations 184, 190, as described above. For example the applicationlayer 204 can be used to provide a graphic user interface 151 of aclient workstation 184,194 a user-interactive interface.

In another example an external database 204 can provide speed and ortraffic data which records data for posted speed limits along routes, orcollects and stores data for average traffic speeds along routes.Exemplary databases include, for example, the TeleAtlas™ speed limitdata, or Inrix™ average speed data. This data can be used in conjunctionwith GPS data 211 and business logic 204 to show speed violations ofvehicles and drivers, compare average speeds of a driver's and/or afleet's average traffic/road speed, and track performance and createalerts as described herein.

An applications layer 204, such as an application sever 204, can be usedto run applications processing, which may include, for example, sendingdata to and/or receiving data from one or more other data sources suchas client workstations 184, 190, as described above. For example theapplication layer 204 can be used to provide a graphic user interface151 of a client workstation 184,194 a user-interactive interface.

In one embodiment, a system is configured to received, store, andprocess GPS data to provide to a graphic user interface of a client auser-interactive interface for tracking and reporting on vehicles andvehicle fleets. For each vehicle, GPS event data is stored for over anoperation period. For example, the data can be stored and processed toshow event data for at least one vehicle v for an operation period of aworkday, a week, a month, a quarter, a year, the life of a servicecontract, or any desirable time period. The GPS event data can then beanalyzed to derive a plurality of operational metrics for each vehicle.Exemplary operational metrics that can be derived from GPS data include:engine on/off, vehicle mileage, idling, number of stops, distancetraveled, and speed (including high speed and average speed). Forexample, an on-board GPS device can be configured to be operational totransmit when a vehicle engine is on, thus engine on/off time can bederived. Idling (stopped while engine running) and speeding(distance/time), as well as vehicle mileage can also be derived fromtracking via GPS. This data in turn can be used to derive a number ofother operational metrics, including vehicle activity over apredetermined time period, vehicle operational reports, employeeperformance (e.g., working hours, deliveries per day), driver behavior(e.g.: speeding violations, idling over limits); and fleet performance(e.g., metrics based on data above derived for multiple vehicles).Accordingly any number of operational metrics can be derived from GPSdata, either alone or in conjunction with data from other databases,including number of stops per vehicle, performance against a criterion,employee performance; driver behavior; and fleet performance, speedingseverity, a speeding violation, average vehicle speed, vehicle speedversus a posted speed limit, vehicle speed versus a speed threshold, andan average road speed for a fleet or driver speed for a route versusaverage road/traffic speed for a route. A graphic user interface can beconfigured to display including a representation of at least oneoperational metric for each of a plurality of vehicles.

Exemplary graphic representations or interfaces 300 for a graphic userinterface for a user is shown in FIGS. 3A-3T. Such interfaces could bein the form of application software for computer and digital devices asdescribed above, or in the form of webpage accessed by a client from atleast one host server, or any combinations thereof as broadly disclosedherein and without limitation. As shown in FIG. 3A, a “Dashboard” 320page gives a user a first interactive screen to view GPS data andoperational metrics. The top of the graphic user interface 300 has, inone embodiment, tabs for “Reports” 320, “Live Fleet,” 332 “RouteReplay,” 324 “Alerts,” 328 Fleet Service,” 330 and “Admn” 332, whichlead to other user interactive displays. Of course any number of tabs orlinks could be configured for the features as described herein, forexample for “Speed” “Trending,” “Score Card,” and/or A “MyFleetmatics”or “My Fleet” page which can include user configurable fleet statisticsand alerts, or can have default statistics personal to a user, or somemix of user configurable and default features and statistics.

For example, in one embodiment a user can select “Live Fleet” 324 usingan input such as a keyboard or a mouse, which would lead to a page withGPS data and mapping software which tracks vehicles v1, v2 . . . vn. Thepage can allow a user such as a dispatcher to, for example, locate anddispatch the closest vehicle to any job site and reroute the nearestvehicle.

The Dashboard 320, as with any other screen, can be configured to offerpreset modules or objects for a user to interact with or view, or in thealternative it can be configured to allow a user to customize theinformation, reports, alerts, etc most important to the user. Forexample, an exemplary “Dashboard Preferences” page is shown at FIG. 3B,which allows an administrator user to “drag and drop” icons toconfigured the order of graphs for operational metrics of Engine On/Off335 a, Distance Traveled 335 b, Idling Report 335 c, and High SpeedReport 335 d “Speeding Violations,” 335 i and “Speeding Severity” 335 has desired.

As shown in FIG. 3A, the Dashboard 320 screen includes various graphicrepresentations of operational metrics, including reports and alerts, toaid a user in, among other things, vehicle, employee, and fleetmanagement. For example, the operational metrics 302 for individualvehicles include operational metrics such as a engine on/off 302 a,vehicle mileage 302 b, idling, 302 c, and speeding 302 d. Otheroperational metrics could also be shown such as average speed 302 e,number of stops 302 f, speeding severity 302 h, and speeding violations302 i. Such operational metrics are also shown for various fleetconfigurations as described below.

The Dashboard 320 shows at the top of the interface 300 a graphicinformation display for an individual vehicle 301, which can be selectedfrom a drop down menu 301 a. Other methods of selection can be used, forexample, by selecting with a mouse, a graphic for the vehicle v4 (shownas “Van 1006”) in a fleet report graphic 335. The graphic informationdisplay for the vehicle 301 includes a reporting and alerts for thevehicle v4, for example, operational metrics such as at least one engineon/off graphic 302 a, vehicle mileage graphic 302 b, idling graphic 302c, and a speeding graphic 302 d.

As shown, the graphics 302 a, 302 b, 302 c, 302 d on the individualvehicle 301 is shown reporting graphic that shows a rating 303 undereach operational metric comparing the vehicle performance against othervehicles in the fleet for a 24 hour period. For instance, an engineon/off rating graphic 303 a puts the vehicle v4 in 4^(th) place in thefleet, a vehicle mileage rating graphic 303 b puts the vehicle v4 in6^(th) place, idling rating graphic at 303 c at 19^(th) place, and aspeeding rating graphic 303 d puts the vehicle v4 at 7^(th) place. Thesemarkings for v4 are also seen in the fleet management graph 335 a, 335b, 335 c as described below.

The interface 300 also provides, for the graphic user interface, analert when an operational metric for a vehicle exceeds a predeterminedthreshold established for the operational metric. For example, reportgraphic on the individual vehicle 301 shows the name of the driver, thatthe vehicle has shutdown (e.g.,: for the end of the workday), the timefor shutdown, and for each of the operational metrics, a pie chartgraphic 305 a, 305 b, 305 c, 305 d, and a split-window graphic 306 a/308a, 306 b/308 b, 306 c/308 c, 306 d 8/308 d 8/309 d for the individual'sengine on/off, vehicle mileage, idling, and speeding graphicsrespectively, each of which are designed to alert and report to a userwhen a vehicle has exceeded a predetermined criterion such as apredetermined threshold. Each of the pie chart 330 and split windowgraphics 306/308 show the time the vehicle spent within threshold 306,as well as a representation that alerts when the vehicle exceeded thethreshold. For example, each metric has in the split window graphic306/308 a predetermined criterion or threshold 306 established for the24 hour period: 8 hours for engine on/off 306 a, 150 miles for vehiclemileage 306 b 8/308 b, 1.0 hours for idling 306 c/308 c, and threespeeding thresholds of over 70 mph, 80 mph, and 90 mph under speeding306 d 8/308 d 8/309 d.

For example, the “Engine On/Off” split window 306 a/308 a has in aleft-hand window, for vehicle operation within the predeterminedthreshold 306 a, a graphic which includes a color (green) and textdescribing the vehicle's v4 operation statistic under the threshold, 7hours, 50 m. The right-hand window 308 a, shows a window with the timeremaining in the 24 hour period (16 hours, 10 min.) Because this is timewhere the engine was not running, and thus within the threshold, thewindow 308 a is configured to show neutral color or identifier (e.g.white, tan, clear). The pie chart 305 a shows a visual with green andneutral coloring corresponding to the times in the split window 306a,308 a which allows a user to readily visualize the percentages for theEngine On/Off time.

The “Vehicle Mileage” split window 306 b/308 b shows the predeterminedthreshold of 150 miles in the left-hand window 306 b, which is in greenas with Engine On/Off. However, the right-hand window 308 b shows thedriver has exceeded the threshold by another 38 miles. As this is inexcess of the threshold, where the window 308 b is configured to alertthe user with a red color. The pie chart 305 b shows a visual with greenand red coloring corresponding the times in the split window 306 b, 308b which allows a user to readily visualize the percentages for thevehicle mileage, as well as alert the user that the vehicle is excess ofthe threshold.

The Idling and Speeding graphics are similarly configured, therebyproving a user friendly view for all the metrics for the individualvehicle and driver. For example, Idling 302 c includes an alertingthreshold where of 1 hour, and alerts for excess of an hour of idling.Speeding 302 d includes reporting and alerting for, among other things,speeds in excess of 70 mph 306 d, 80 mph 308 d, and 90 mph 309 d, withdifferent colors for each (e.g. green, yellow, and red).

It will be understood that other graphical displays could be used, suchas bar graphs, gauge icons, whimsical graphics (e.g., a speedometer or astopwatch), or any other such graphic as is useful.

For each vehicle v1, v2, v3 . . . vn, historical GPS event data can bestored, as for example, for a plurality of operation periods.Accordingly, while the graphics 302 a, 302 b, 302 c, 302 d on theindividual vehicle 301 are over an operational 24 hour period, thegraphics could be configured to show data for longer periods and/or aplurality of operational periods, such as a week, a month, a quarter, ayear, or other periods as desired. Other thresholds could be implementedfor each of these periods, as for example, by adding the criteria orthresholds for each operational period, e.g., for Vehicle Mileage 302 b,or an 160 hour threshold for a 4 work-week period (a five day week),where each 24 hour period is 8 hours. Other reports can be generatedbased on the historical event data.

For example, report information can include one or more reports on:vehicle activity over a predetermined time period, speed (including highspeed and average speed), number of stops, idling, vehicle operationalreports, maintenance, employee performance, driver behavior; and fleetperformance.

An exemplary, selectable “Top 10” fleet report 335 shows reports 335 a,335 b, 335 c, 335 d for the top ten vehicles in each of operationalmetrics for a fleet of vehicles: Engine On/Off 335 a, Distance Traveled335 b, Idling Report 335 c, and High Speed Report 335 d. As noted hereinadditional metrics for “Speeding Violations,” 335 i and “SpeedingSeverity” 335 h can be added to the reports relating to speed.Operational metrics for one of the vehicles v4, “Van 1006” is shown atthe top of the graphic user interface 301, and the vehicle rankings asshown for v4 are shown in three of the metrics 335 a, 335 b, and 335 dwhere the vehicle is in the top 10, as described above. While the reportshows the “Top 10,” a selectable drop down menu 308 b allows a user toselect any number of options for reporting (e.g., top 20, 50) andanother drop down menu 310 allows a user to select time periods (e.g. 24hours, 5 days, a month), to obtain ranked vehicle performance for thefleet and vehicles therein.

The “Engine On/Off Report” 335 ranks the vehicles v1 . . . v10 fromhighest to lowest for “Engine On” time over the 24 hours. For example, arow for the top vehicle v1 shows the engine was on for 9 hours and 58minutes and off for 15 hours and 2 minutes. The lowest ranked v10(Vehicle 0435) shows engine operation for 6 hours and 8 minutes, whereasthe off time is 17 hours and 52 minutes. A fillable bar graph shows onand off times, with “on” being green and off being blank or neutral,with the fill line visually showing the percentage of the 24 hourperiod. Text graphics write out the time. The rows of bar graphs foreach vehicle are aligned in a columnar format so as to readily compareeach vehicle's statistics with one another.

The “Distance Traveled” 335 b reports and alerts are consistent withcriteria for the “Vehicle Mileage” 302 b for the individual driverdescribed above, and ranks vehicles within the top 10 of the fleet fromhighest to lowest for distance traveled. A fillable bar graph shows thepredetermined threshold of 150 miles in the left-hand bar graph, whichis in green. However, the left-hand of the bar graph shows, with filllines by percentage, where the driver has exceeded the 150 milesthreshold. The top ranked vehicle of the fleet is in excess of thethreshold by 236 miles, whereas the 10^(th) ranked vehicle (Van 1026) isonly a few miles over. A fillable bar graph shows distances times, withthe 150 mile threshold being green any excess mileage being red so as toalert the user, with the fill line visually showing the percentage ofthe 300 mile distance. Text graphics write out mileage at or under 150miles on the left-hand side, and mileage in excess right hand side.Again, rows of the bar graphs for each vehicle are aligned columnarformat so as to readily compare each vehicle's statistics with oneanother. The “Idling” 305 c and “High Speed” 306 d reports graphics aresimilarly configured, thereby proving a user friendly view for all themetrics for the ranked vehicles and drivers in the fleet. For example,“Idling” 335 c includes an alerting threshold of 1 hour, and reports,bar graphs, alerts for excess of an hour of idling. As shown in FIG. 3C,such a Idling report can also be configured in a format for delivery toa PDA or smartphone, which shows bar graphs, rankings, and idling timesfor a plurality of drivers/vehicles over a 24 hour period. Returning toFIG. 3B, as with the individual report 302 above, speeding 335 dincludes bar graphs, reporting and alerting for, among other things,speed in excess of 70 mph, 80 mph, and 90 mph, with different colors foreach (e.g. green, yellow, and red).

More detailed reports can be created and configured. In one embodiment,as shown in FIG. 3C, preferences for speed related metrics (e.g. highspeed 302 d, average speed 302 e, speeding severity 302 h, and speedviolations 302 i) reporting and alerting for the Dashboard can beconfigured by a user from a “Speed Tab.” As shown in FIG. 3C, a user canselect “Speed” from a preferences menu or side bar of links 501 to otherpages (e.g. “Industry Benchmarking,” “Idling,” “Distance Traveled.” Thepage comprises input interfaces 502, 504, 505, 506, 508, 510, 512 foractivating and configuring the display of operational metrics 302 forspeed and speed data, including speed data from speed databases andconfiguring thresholds. An upper graphic interface includes an input 502for activating an average speed for vehicles in a period, which asks“What average speed is too high during a 24 hour period. The input areafor the average speed threshold also includes a slider bar 504 forconfiguring the desired average speed, although any known input methodcould be used. In a second input area, a user can activate 504 andconfigure 505 different speed thresholds for the fleet, for example a“low” 80 mph, 95 mph 308 d, and 110 mph). The user can be given adropdown list 505 with any number of preset thresholds, for exampleincluding higher speed thresholds (e.g, 95 kmph, 115 kmph, 125 kmph)along with the “low” one given above. A third input area allows a useractivate and configure the system interface to include alerts usingspeed limit data, such as posted speed limits and/or or average roadspeeds. Activation interface object 506 allows the user to configure thesystem to include road speed data when showing speed limits Activationinterface object 508 allow show exceptions on pages throughout theuser's interface with the system 508, and another interface object 510,shown as a slider, allows the user to adjust the criteria or thresholdsfor showing exceptions, shown in FIG. 3C to allow the user to adjust thespeed over the road specific speed limit is allowed before flagging anexception (e.g. 0-110 mph). Another activation interface object 512 andslider 514 allows a user to activate and adjust the threshold for theacceptable number of speed limit violations for a given period (e.g.0-150 in a 24 hour period). Yet another input interface 518 allows auser to configure the type of graphic they would prefer to see foralerts, here shown as a speedometer graphic showing and a bat graphicfor the speed reporting graphic, described below, along with a previewgraphic 516 for the choice selected. Once the user has configured thesystem for preferred speed alerts and reporting via the speed tab 500,one or more interface objects 520 allow the user to save the changes forthe configuration and, if desired, continue.

As noted above, the user the user is presented with a graphic 521 and aspeedometer graphic 522 which display alerts for speeding severity ofvehicles 302 h as well as speeding violations 302 i shown in FIG. 3D.

An exemplary, selectable “Speeding Severity” 302 h for fleet reportinggraphics 521, 523 selected from a drop down menu 522 for operationalmetrics 302 a . . . 302 i shows the number of times drivers v1 . . . vn(e.g, at “Top 10”) violated the speed limit thresholds configured, forexample, as set by the user (see FIG. 3C, 510, 12) “How fax over theroad specific speed limit can your vehicles go before they areflagged?”). The report 521 ranks the vehicles v1 . . . v10 from highestto lowest for speeding events over the 24 hours. Finable bar graphs foreeach vehicle v1 . . . vn reporting and alerting for, among other things,speed limit events in excess of posted speed limits by 0-10 KMPH/0-5MPH, 10-25 KMPH/5-15 MPH 25+ KMPH/15+ MPH, with different colors foreach (e.g. yellow, orange, and red). A tally area 525 in the fleetspeeding severity report 521 tallys the number of speed violations for agiven vehicle (e.g. 53 0-10 mph violations, 57 10-25 mph violations, and53 over 25 mph violations, and 163 total violations for vehicle v1),which can be populated when the user selects that vehicle on the graph,for example my a mouse click or mouseover. The speedometer graphic 522shows the total number of speed limit events for a number of vehicles inthe fleet (e.g the top 5, top 10, all), which can be configured tocorrespond to the bar graphic 521 as shown. Speed limit events in excessof posted speed limits by the vehicles are shown as 0-10 mph, 10-25 mph,and over 25 mph, with different colors for each (e.g. yellow, orange,and red) on a 0-350 “speedometer” semi-circle. A tally area 523 at thetop of the graphic in the fleet speeding severity report 521 tallys thenumber of speed violations for the vehicle group (e.g. 240 0-10 mphviolations, 57 10-25 mph violations, and 53 over 25 mph violations, and163 total violations for vehicles v1 . . . vn).

An exemplary, selectable “Speeding Violations” 302 i for fleet reportinggraphics 526, 528 selected from a drop down menu 522 for operationalmetrics 302 a . . . 302 i shows the number of times drivers v1 . . . vn(e.g, at “Top 10”) violated the speed limit thresholds configured thistime showing the number of violations vs an acceptable number ofviolations, for example, as set by the user (see FIG. 3C). The firstreport 526 ranks the vehicles v1 . . . v10 from highest to lowest forspeeding events over the 24 hours. Finable bar graphs fore each vehiclev1 . . . vn reporting and alerting for, among other things, acceptablespeed limit violations and those exceeding the threshold (e.g. greenred). A tally area 527 in the fleet speeding severity report 526 tallysthe number of speed violations for a given vehicle (e.g. 15 allowedviolations, 12 excess violations, and 27 total violations for vehiclev1), which can be populated when the user selects that vehicle on thegraph, for example my a mouse click or mouseover. The speedometergraphic 528 shows the total number of speed limit events for a number ofvehicles in the fleet (e.g. the top 5, top 10, all), which can beconfigured to correspond to the bar graphic 526 as shown. Speed limitevents in excess of posted speed limits by the vehicles are shown asacceptable and in excess, with different colors for each (e.g. green andred) on a 0-350 “speedometer” semi-circle. A tally area 529 at the topof the graphic in the fleet speeding violation report 521 tallys thenumber of speed violations for the vehicle group (e.g. 150 acceptableviolations for 10 active vehicles) and, a pointer on the “speedometer”shows the level of violations.

FIG. 3E shows another example of a detailed report for an employee andvehicle, as could be accessed, for example, in a page for reports (seeFIG. 3A 322). The report is an “Hours Worked Report” 350 for a vehicle(Truck 18) over a five day workweek, as shown in the lower table 340portion of the graphic user interface 340. Each day of the work week isgiven a row 340 a, 340 b, 340 c, 340 d, 340 e on the report, and thetable 340 which includes columns for day, start time, driver, finishtime, and an “Hours Worked” bar graph 344 a, 344 b, 344 c, 344 d, 344 ewhich shows a colored fill bar and text showing the hours worked. Thereport has alerting icons E1, E2, E3, E4, which show exceptions where avehicle and driver have exceeded predetermined thresholds or criteria.The exception alerts are described in an upper window 342, which can bescrolled using a scrolling graphic 343 using a mouse, via touch screen,or other input. The upper window 342 reports and alerts the user as tothe exceptions, which reports two alerts 306 b, 306 c that on 2 days adriver finished at 1:22 pm and 1:30 p.m., which is before predeterminedtime (before 4:00 p.m.). Another alert 306 a shows that on one day thedriver worked two hours longer than a predetermined time period (12hours), as the driver worked 14 hours and 33 minutes. By scrolling downthe upper window module 342, the user can see the fourth alert for theexception E4, where the driver exceeded the predetermined threshold of12 hours by 27 minutes. The fill bars on the bar graphs 340 a, 340 b,340 c, 340 d in the lower table 340 can also be colored to reflect analert, such as where on days where a driver has exceeded thepredetermined threshold for hours worked E1, E4. For example, the fillbar 344 b, 344 e can be colored red when the predetermined threshold isexceeded, whereas when under the threshold, the bar 344 a, 344 c, 344 dis colored green. A week summary portion 346 of the graphic userinterface 350 can give over all statistics for the week, such as startand finish dates and times, total hours and days, and average hours perday.

FIG. 3F shows a example of a detailed report for an employee andvehicle, as could be accessed, for example, in a page for vehicle speedsand violations. The report is a “Red Flag” report 600 for points ofinterest (POI) for a vehicle (“Phil”) over a workday, as shown in thelower table 602 portion of the graphic user interface 340. The reportcan be configured by a user to cover any time period by a number of dropdown menus 604, 605 f or selecting a begin date time 604 and an enddate-and time 605, each including drop-down menu for month, date, andtime. Also included is an option 606 to select or deselectMonday-Sunday, so as to exclude or include specific days (e.g. toinclude only the driver's working days). Also included is an interfacegraphic 603, for example radio buttons, for selecting the parameters forthe report, shown as being configured to show events over a given mphinput by the user, or events where the report is a given MPH over aspeed limit. It will be noted that the display can be configured to KMPHwhere that is the proper or desired metric. As shown in FIG. 3F, thereport is run for events that are 2 mph over a speed limit for aworkday. If the first radio button option is checked the text in theType column results should read “Speed Above X MPH (or KMPH)”. If thesecond radio button option is checked, then the text should read “PostedSpeed” or “Road Speed” or “Average Speed” or “Traffic Speed,” or“Trusted” or other such name as may be chosen, depending on the type ofposted speed limit available. Once the report inputs are set, the reportis run via a “Run” 605 tab, which shows all locations for that timerange for which the driver went at least two mph over a posted speed oran average traffic speed.

On the list, the table 602 which includes columns for day 611, time 612,“Type,” 613 “Details” 614 and a “Flag” 615 for MPH. The day 611, time612, and details 614 columns show the date, time, and location of thedriver (Phil) at points along a route. In the “Type” 613 column is adesignation showing the type of criteria for the Red Flag report 600alerting, in this embodiment, shown as “Trusted,” indicating a trustedposted speed limit for this route, or “Average,” indicating the reportand/or alert is for the average traffic/road speed for the location. Thereport has alerting icons E1, E2, E3, E4, E5 which show exceptions wherea vehicle and driver have exceeded predetermined thresholds or criteria,shown here as speeds in excess of a “posted speed” for a route or theaverage road speed for the location. The exception alerts E1 . . . E5are described in a window 608 above the table 602, which can be scrolledusing a scrolling graphic 609 using a mouse, via touch screen, or otherinput. The window 602 reports and alerts the user as to the exceptionsE1 . . . E5, which reports the 5 exception alerts explaining that thespeeds (1.) 67 (2.) 69 and (3.) 65 MPH are each above the posted speedfor that location. By scrolling down the upper window module 609, theuser can see the fourth and fifth alert for the exceptions E4, E5, wherethe driver exceeded the speed limit (68 mph and 64 mph).

The “Flag(mph)” 615 column in the table 602 shows the driver's mph at alist of locations, shown in the “Details” column. Speeds in the “Flag”column can be rounded up/down. Also shown for each exception E1 . . . E5is the driver's mph at the location in red and an icon, a red circlewith the number “60,” indicated that the posted speed for that locationis 60 mph. A “mouse-over” can also display text with further detailswhen a pointer is placed on an exception.

Other icons can include reporting and alerting for, among other things,speeds in excess of speed thresholds 70 mph 306 d, 80 mph 308 d, and 90mph 309 d, with different colors for each (e.g. green, yellow, and red)for as shown in a driver's speed graphic 610.

FIGS. 3G-3J shows another example of a detailed report for an employeeand vehicle, shown as a “Scorecard” for a driver. As shown in FIG. 3G, aleft hand graphic 307 includes fillable bars like those in FIG. 3A thatshow, for a driver, a score card for operational metrics Average Speed302 e, Distance Traveled 302 g, Engine On/Off 302 a, Vehicle Idling 302c, High Speed 302 d, Number of Stops 302 f, Average Speed 302 c,Speeding Severity 302 h and Speeding Violations 3 i for the individualdriver. A ranking for each metric as compared to other vehicles in thefleet is also given. The GPS data analysis is given for a time period,for example 5 days (FIG. 3G) or 24 hours (FIG. 3I). As shown in FIG. 3G,on a right-hand graphic 311, a bar graph shows, for each day of the 5days, an average speed, where the X-axis has each day, and the Y-axisshows miles per hour (0-60 mph). As shown in FIG. 3I, on a right-handgraphic 311, a bar graph shows, for each hour of the 24 hours, anacceptable and an excess speed over a speed limit (e.g., posted oraverage), where the X-axis has hours, and the Y-axis shows miles perhour in excess (0-15 mph); bars are colored as described herein todistinguish speeding thresholds. FIG. 3H shows a scorecard graphicconfigured for an application for a PDA such as a smart phone, similarto the left-hand graphic 307, showing a score card for operationalmetrics 302 a, 302 g, 302 c, 302 d, 302 f, 302 e, 302 h, 302 i for theindividual driver, as well as a ranking for each metric as compared toother vehicles in the fleet, for a time period of 24 hours.

Still other reports based on GPS data and tracking could be provided,such as driving behavior including vehicle speed, engine start-up andshut-down and idling time, or any others including as described hereinwhich can be used to enforce driving policy and curb unwanted behaviorlike excessive speeding, tardiness and extended vehicle idling.

Similarly, alerts based on GPS data and tracking could be generated suchas alerting a user immediately if a vehicle is used during off-hours,which can indicate a vehicle theft. Other exemplary alerts include latedeliveries, vehicle case or maintenance is needed, or area reportingand/or need for rerouting. For example, alerts can be triggered forexcessive speeding, excessive idling, engine start-up or shut-downduring off-hours unauthorized vehicle usage and when a vehicle enters orexits specific geographic areas. Alerts can also be configured to alertwhen vehicles are due for scheduled maintenance (e.g., based on aspecific length of time, miles driven, or engine-on time). Alerts canalso be segregated from reporting on a separate page of a graphic userinterface (e.g. accessible by a tab 328 as shown on the Dashboard 328 atFIG. 3A).

Alerts can be flagged in relevant reports as shown above, and users canalso be notified of any alerts as soon as a violation occurs via emailor mobile device. As shown in FIG. 3F, it will be noted that in someembodiments, a portable device such as a smart phone or PDA can beconfigured to receive alerts that need urgent attention, such as anoff-hours use alert or an alert indicating rerouting is needed. Forexample, as shown at FIG. 3J, an application is configured to show anumber of alerts 315 received over a course of time, including forexample, alerts showing a speed criterion or threshold has been met orexceeded. By selecting one of the alert indicators, a separate detailsscreen 317 is accessed which describes the alert. As shown at FIG. 3K isa page for allowing a user to configure a speed threshold alert. Userinterface icons, shown as radio buttons 536, 543 in place for users todecide how to display the alerts, “Alert at Speed X mph/kmph 536 and“Alert Speed Violations when at least X over limit 538. If the “AlertSpeed Violations” 538 is checked a second option (check box) willactivate; “Use Average Road Speeds at limits when needed.” This optionwill use average speeds for a route if the exact posted speeds are notavailable. A scheduler 545 area allows a user to schedule days and timesfor the alert, and an “Alert Recipients” 552 area allows a user todesignate recipients and can further be configured to designate themethod of contact (e.g e-mail, text, etc.).

Reports or alerts can also be configured to how fleet alerts 390 for afleet trending data 390, as described below.

As explained above, the computer system includes GPS event database. TheGPS event data is analyzed to derive a plurality of operational metricsfor each of a plurality of vehicles; and identify, from the analysis, atleast one trend for a GPS event history using the GPS event data. Thesystem can be configured to provide to a graphic user interface aninteractive display configured display a representation (e.g., a graphicpresentation of the trend). Reports and alerts based on GPS data andtracking and trending is provided, including for driving behaviorincluding vehicle speed (including average speed and high speed), enginestart-up and shut-down, idling time, number of stops or any othersincluding as described herein which can be used to enforce drivingpolicy and curb unwanted behavior like excessive speeding, tardiness andextended vehicle idling.

A description of systems and methods for accumulating and presentingdata for GPS data for a fleets and vehicles, including for operationalmetrics and trends, can be found in U.S. patent application Ser. No.13/097,689 entitled SYSTEM AND METHOD FOR PROVIDING VEHICLE AND FLEETPROFILES AND PRESENTATIONS OF TREND, the entirety of which isincorporated by reference herein.

FIGS. 6A-6C shown a graphic flow for analyzing received GPS event dataand GPS data stored over time to identify, report, and display trending.As shown in FIG. 6A, GPS event data for each vehicle, as describedherein, is gathered over a period of time. The data is analyzed for overtime (shown over 6 months) derive operational metrics 302, for example,mileage 302 b, speeding, 302 d and idling 302 a. Trending can also bederived and displayed for other operational metrics as described herein,including speed severity 302 h, speed violations 302 i, number of stops302 g, or other such metrics as are or become available using data fromGPS events and external databases. Such data can be analyzed for eachmonth to identify statistics for each operational metric, for example,for each vehicle or employee, as well as to derive statistic for thefleet (e.g. averages under each operational metric, or averages fordefined groups under each metric). Such data can be collected and storedindefinitely.

As shown in FIG. 6B, the analyzed historical event data for eachoperational metric 302 shows trend data 362, for example, theperformance of a vehicle/driver v over the 6 month period, for example,a mileage trend 362 b, a speeding trend, 362 d and an idling trend 362 afor each month. As shown in FIG. 6C, the trend data 362 for eachoperational metric can then be extrapolated from the GPS event data.This trend data is extrapolated for each vehicle in a fleet, as well asfor each employee, and can be used in conjunction with other databasesto provide trending and statistical data as described herein. Trend dataincludes not only the direction in which performance and behavior moveunder operational metrics, but also identifiable changes in thosemovements and comparisons therebetween, as well as statistical datadrawn from GPS data and other databases, as described herein.

In one embodiment computer system the GPS event database includes a peercomparison database including peer comparison data associated with thevehicles. The system also includes a credibility criterion. The GPSevent data includes location information for the vehicle, which isstored in the GPS event database. Operational metrics for the GPS eventhistory are derived for a trend including a trend for peer comparison. Arepresentation including a representation of the peer comparison for atleast one operational metric can then be provided to a graphic userinterface. The operational metric can include metrics described herein,including those selected from the group of engine on/off, vehiclemileage, idling, speed, performance against a criterion, employeeperformance; driver behavior; industry segment performance, geographicalarea performance, and fleet performance. In one embodiment the peercomparison data comprises geographic data associated with the vehicles;and industrial data associated with the vehicles.

In one embodiment, the computer system comprises: a thresholdcredibility criterion for GPS event data used for a peer comparison.Data acquisition is as follows. GPS event data is acquired and storedfrom GPS devices with vehicles as described herein. GPS event data forthe vehicle is associated with a peer comparison parameter. When GPSdata for a statistically significant number of vehicles for a peercomparison parameter is reached, the system can then elevate that peercomparison metric for display for a user. Both previously storedhistoric GPS event data can be associated with a parameter, as well asincoming GPS event data.

In one embodiment the threshold criterion for statistical significanceof peer comparison is a Standard of Full Credibility of at least 1,082vehicles. This number indicates a 90% probability (P) that estimate iswithin tolerance K=5% of a true value. The Standard of Full Credibilityis based on a unique vehicles count for a period of time. In oneembodiment, the period of time is a calendar month, excluding a currentday (as described in more detail below). The criterion can also includea maintenance credibility criterion. For example, after the thresholdcriterion has been met in a given period, the system can be configuredto maintain showing peer comparisons for users in subsequent periods solong as the maintenance criterion is met. In an embodiment, amaintenance criterion can include a Minimum Criteria of at least 60% ofthe threshold criterion, for example, a Standard of Full Credibility(SCF)=390 vehicles.

Processing frequency as in one embodiment is now described. The computersystem creates a periodic record of the GPS event data stored for thevehicle. For example, in one embodiment, GPS event data as received andprocessed daily. The system can further process the data to show anaverage operational metric for a plurality of the vehicles over a periodof time, for example monthly or quarterly averages on trending ofoperational metrics. In one embodiment, peer comparison average valuesare updated as follows. In a “Current Month,” current month values willare updated with daily processing A Current Month can begin to bepublished starting with a given day, for example day 7 of a week. Filtercriteria can be applied to, for example round out to a week or to offsetfor holidays and weekend, as described below.

As explained herein, previously stored historic GPS event data can alsobe associated with a parameter. In one embodiment, historic peercomparison values are processed. In “Historic Months,” Historic monthvalues do not change once published at month-end. Month-end finalaverage values are be reviewed before they are published to preventillogical values. In one embodiment, once a decision has been made tomake available a specific peer comparison for a Historic Month(s), atthe point of initial elevation there are published at least 3 datapoints (3 monthly averages) to make trending comparisons relevant. Aftera peer comparison has been elevated, monthly averages will be publishedwithout any gaps even if the number of vehicles during a month fallsbelow the maintenance criteria (e.g. the Minimum Criteria describedabove).

In one embodiment the computer system comprises a filter criterion suchas a filter rule. For example, in an embodiment the system comprises afilter rule and/or includes an outlier exclusion. The filter criterioncan be configured to filter any periodic records meeting a filtercriterion.

in one embodiment, a filter rule excludes vehicles from the criterioncalculation. For example, in an embodiment, a rule excludes outliervehicle-clay records from a monthly average calculation. For example, arule is configured to exclude vehicle-day records where a vehicle drovevery little or too excessively relative to a vehicle Mean for the month.In an embodiment, a Local_Ratio of vehicle-day driving is used as theMEAN metric; which gives a measure of meaningful driving and considersboth driving radius and mileage (mileage/“Distance_Between_POINTS”:i.e., which tends to exclude excessive long range or very short drivingusing a Local Ratio concept.

Filter rules can exclude periodic records (described below) based withthe following attributes: Idle time—vehicle-day records with more than10 hours of idle time; and On/Off engine—vehicle-day records with morethan 20 hours. An outlier calculation is configured as follows: On adaily basis, for Current Month obtain a “Local Ratio” values for eachavailable vehicle-day that passes the Filter Rules. For Current Month—ifavailable, use the vehicle-day mean and standard deviation calculated atend of previous month (as described herein); else, if there is no meanand standard deviation available use all records from current month(i.e., for a new or seasonal business). At month-end the MEAN andStandard Deviation for Local Ratio for all the observations availablefor the month are calculated for vehicles that had at least 5 days ofdriving activity Outlier records that have Local Ratio greater or lessthan 2 STD DEV from the Mean; around 89% of records would still remainin the dataset, as shown in FIGS. 5A-5B.

For example, in one embodiment, a rule engine is configured as follows:

Stage 1

-   -   01. Does company want to share data? (Default—Yes)—User table        flag check    -   02. Local Ratio>1Local Ratio=Null    -   03. Idle Time>10 Hours    -   04. Engine On Time>20 Hours    -   If a periodic summary fails any of the above, the vehicle day        summary is not included, and the analysis moves to the next        vehicle.

Stage 2

-   -   01. Check last month's number of days≧5 (if the vehicle summary        fails this one, it is to be included in the statistically        significant sample.)        -   Finally, the local ratio is compared with last month's mean.            If a daily record is 2 STD outside of the mean it is            excluded. Otherwise, the vehicle is included in the count.

In one embodiment the system is configured to identify a trend for anoperational metric for the plurality of vehicles, the operational metricincluding an operational metric selected from the group of: engineon/off, vehicle mileage, idling, speed, performance against a criterion,employee performance; driver behavior; industry segment performance,geographical area performance, and fleet performance. The computersystem is configured to identify at least one trend for a peercomparison for the operational metric from the periodic records. Thepeer comparison includes a peer comparison metric. The peer comparisonmetric includes a peer comparison parameter selected from the groupconsisting essentially of a geographical parameter and an industrialparameter.

In an embodiment the industrial parameter is an industrial segment.Exemplary industrial segment data is data associated with a vehicle,such as an SIC code associated with a fleet of vehicles. For example,the system can be configured to the use an SIC match to associatevehicle activity with a specific Industry Segment. In one embodiment,the system includes a number of different industry segments. Forexample, as shown in Table 1, the system includes 12 different IndustrySegments & All Industries combined. However, as will be understood,industry segment definitions can include and be further broken down intosubspecies or combined into broader genus or parent segments to processaccumulated GPS event data.

TABLE 1 INDUSTRY SEGMENT 1 1. Plumbing, Heating, Air-conditioning 2 1.Electrical Work 3 1. Disinfecting and Pest Control Service 4 1. For HireTrucking, Except Local 5 1. For Hire Trucking, Local 6 1. Landscapers 72. Delivery 8 2. Home & Business Field Service 9 2. PassengerTransportation 10 3. Contractors Heavy 11 3. Contractors Light 12 3.Specialty Transport 13 4. All industries

In an embodiment a periodic record is created of the GPS event datastored for the vehicle, and an industry segment identifier associatedwith the vehicle is linked to the periodic record. A plurality of theperiodic records for vehicles are processed to determine if a number ofvehicles meets a credibility criterion for a peer comparison analysis.For example, periodic records such as daily summary records are linkedto an SIC code, and that SIC code is matched to a single industrysegment. In one embodiment, a single SIC code comprises its own peercomparison industry segment, however, it may also be linked to a broader“Parent” industry segment for use (e.g., for later use). For example, anSIC code SIC 1711 “1. Plumbing, Heating, Air-conditioning” is one of the12 industry segments identified in Table 1, but it could also be linkedto a broader “Home & Business—Field Services,” to be used for ageographical area, such as a state or region as described below, forpresent or later use. A broader industry segment can be defined byand/or configured to cover a number of “species” industry segments, suchas a plurality of SIC codes.

In one embodiment, a filter criterion excludes vehicles from thecriterion calculation. For instance, in an embodiment, a rule excludesoutlier vehicle-day records from a monthly average calculation, asdescribed above.

In an embodiment a periodic record is created of the GPS event datastored for the vehicle, a bounding area is associated with the periodicrecord of the GPS event data for the vehicle and a geographical areaassociated with the bounding area is identified. An industry segmentidentifier associated with the vehicle to the periodic record and aplurality of the summary records are processed to determine if a numberof vehicles meets a credibility criterion for a peer comparisonanalysis.

For example, a location is determined for each vehicle for each day. Thelocation (state or region) for that day should be what is used androlled up when obtaining a value for a particular Region or State. Thevalue that is stored with each record is a shape file, for example, arectangle of lat/long coordinates of a bounding box of the vehicle'sactivity for that day. From that rectangle a center point to use andfind the particular geographic Region or State for that vehicle. Adetermination is made whether the lat/long coordinates are inside theshape file. Default rules can be implemented for illogical results, asfor example if the lat/long coordinates of the bounding box of thevehicle's activity for that day are within a body of water, then thesystem can be configured to default to a physical address for thegeographical area (State or Region).

In one embodiment, the specific geographic areas used for comparisoninclude 5 regions and 6 large states. For example, as shown in FIG. 3T,shows for “Regions” that there are 5 regions: North East, South East,South Central, Midwest and West, and for “States” there are 6 largestates anchor the regions: CA, TX, FL, NY, NJ, IL

For example, regions and states for the accumulation, processing andpresentation of GPS event data can be as shown in exemplary Table 2shown below.

TABLE 2 State St_cd Region State St_cd Region Alabama AL South EastWashington WA West District of Columbia DC South East Connecticut CTNorth East Delaware DE South East Massachusetts MA North East Florida FLSouth East Maine ME North East Georgia GA South East New Hampshire NHNorth East Maryland MD South East New Jersey NJ North East MississippiMS South East New York NY North East North Carolina NC South EastPennsylvania PA North East South Carolina SC South East Rhode Island RINorth East Tennessee TN South East Vermont VT North East Indiana INMidwest Arkansas AR South Central Michigan MI Midwest Louisiana LA SouthCentral Ohio OH Midwest Oklahoma OK South Central Wisconsin WI MidwestTexas TX South Central Arizona AZ West Washington WA West Colorado COWest Connecticut CT North East Idaho ID West Massachusetts MA North EastMontana MT West Maine ME North East New Mexico NM West New Hampshire NHNorth East Nevada NV West New Jersey NJ North East Utah UT West

In one embodiment, the system is configured to provide peer comparisonmetrics including a peer comparison parameter selected from the groupconsisting essentially of a geographical parameter and an industrialparameter. For example the system can be configured with an IndustrySegment—Geography Switchboard. Separate switchboards can be made fordifferent countries or geographical areas.

Based upon the credibility analysis described above, Industry Segmentscan be activated when enough vehicles meet a credibility criterion. Forexample, as shown in FIG. 7, industrial segments are active for peercomparison for specific large States and Regions. In one embodiment, allIndustry Segments will be turned on for both the large States andRegions, with certain exemptions. The exceptions are “For Hire TrucklingLocal and non-Local” are not available for states because these aresegments with regional profiles; all Regions and FL (the only state)have available the Disinfecting and Pest Control Service segment; andall Regions and FL, NJ and NY will have available the “PassengerTransportation” segment.

FIG. 3L shows one example of a detailed trend report 355 for a fleet andemployees from trending analysis as described above, including a peercomparison. As will be understood, the trending analyses can be shownwith or without peer comparison options in various embodiments.

As shown, a “Trending” page could be accessed, for example, in a pagefrom the “Dashboard.” The trending 355 is an “Average Speed” report 355for the average speed 302 e for at least one fleet group 357 over a timeperiod 364, for example 3 months, 6 months, a past year, a selectableyear (e.g. 2010, 2011) or “all” (e.g. a full time period for which datawas collected for a given user). It will be noted that the time periodavailable to a given user depends on how much GPS event data stored forthe fleet for that user. For example, a user whose fleet data iscollected starting Jan. 1, 2011 would not have options for data beforethat time.

A drop down menu 359 is configured to allow a user to select any numberof operational metrics 302 as described herein, for example: AverageSpeed 302 e, Distance Traveled 302 g, Engine On/Off 302 a, VehicleIdling 302 c, High Speed 302 d, Number of Stops 302 f, or Average Speed302 e, Speeding Severity 302 h, and Speeding Violations 302 i, While afleet group 357 is shown as “all vehicle groups,” a fleet group caninclude any subset of vehicles, and can be configured to allow a user toset up custom groups a fleet. For example, a user may have fleets fordifferent geographical locations (e.g. a Bronx Fleet, Brooklyn Fleet,Queens Fleet, a New Jersey Fleet, a Dublin Fleet etc.) then the groupscan be so defined. GPS data can then be filtered and analysed for thisgroup for vehicles within in the group selected in the manner describedabove. The system can also be configured to permit a user to view thetype of statistical data within the operational metric For exampleanother drop down menu 364 allows a user to select either “Averages” or“Totals.” The graphs represent can represent either totals across thefleet or subset selected, or non-zero averages across the fleet. Anon-zero average discounts, for example vehicles who had no data for theperiod, e.g. for fleets who have added new vehicles or decommissionedvehicles periodically in their contract.

As shown in a graph 358 in a top portion of the user interface 355, afleet report for all vehicle groups 364 breaks down the average speedfor all vehicles in a fleet for that year 364 by each month (May, 2010356-5, June 2010 356-6 . . . April, 2011 356-4). As shown, the monthsare along and x-axis whereas the speeds (from 0-10 mph) are along ay-axis. Each of the bars 356-5, 356-6 . . . 356-4 along the y-axis showaverage speed for each month. Bars 356 can be colored to conveyinformation, for example, bar showing the month with the highest averagespeed 356-9 of about 9 mph, is a different color (e.g. blue) than thebars for the other months (e.g. green).

The trend data can include operational performance against at least onecriterion, the at least one criterion including a criterion selectedfrom at least one of: a user-configurable criterion; a criterion derivedfrom GPS event data; a criterion derived from data other than GPS eventdata; a criterion derived from traffic data; and a criterion derivedfrom peer comparison data. As shown, the system is configured to show apeer comparison metric, which can be used as a criterion or benchmark.

While such a criterion can be derived from GPS event data from the fleetfrom that user, it can also be derived from other data such as industrystandard data derived from, for example GPS data of other users orexternal databases that hold data related to operational statistics asdescribed herein. Incorporating peer comparisons into the trendinginformation allows a user to compare the performance of a fleet to thatof an industry or geographic region/type in the same manner as comparinga driver to the overall fleet. A user would thereby be able to compare afleet or group of vehicles, individual vehicles, and an industry orgeographic region.

In one embodiment, the system is configured to provide a peer comparisonas described above. Positioned below a trending graph is an interface371 providing options for comparing the trending that has been chosenfor an Industry or Geographic region/type that is selected fromdropdowns.

An “Industry Type” dropdown 370 provides a user with the ability toselect an Industry they wish to use for the comparison. The options inthis dropdown can include: “All Industries”—an option that allows theuser to only select a Geographic region/type if desired. A list ofIndustries that should be available depending upon Industry selected isshown in FIG. 3L, as described herein.

A “Geography” dropdown provides a user with the ability to select ageographic region/type to use for the comparison. In an embodiment, thisoption can be used in addition to the Industry selection or as astand-alone option (for example if “All Industries” is selected). Theoptions in this dropdown include a combination of regions as well astypes. There may be some separators used within the list to distinguishregions from types. An “All Regions” option allows a user to only selectan Industry to compare. In an embodiment shown at FIGS. 3L-3M a list ofGeographies are available depending upon the Industry selected. Incertain embodiments, not all Geographies will be available for eachIndustry segment. Therefore, the Geography dropdown 372 should besensitive to the Industry that was selected in the first dropdown. Onlythe Geographies that are available for the Industry that was selectedshould be shown.

In an embodiment, between the Industry and Geography dropdowns is a“switch” icon (for example, arrows going left and right), that whenclicked would switch the two dropdowns allowing the user to first selecta Geography and the Industry dropdown would be sensitive to what wasselected as a Geography. Once the user has selected the Industry and/orGeography they desire, they can click the “Apply” button to have thatinformation populated in the Trending Graph and adding to the RankingList.

As shown in a graph 358 in a top portion of the user interface 355, afleet report for all vehicle groups 364 breaks down the average speedfor all vehicles in a fleet for that year 364 by each month (May 2010356-5, June 2010 356-6 . . . April, 2011 356-4). As shown, the monthsare along and x-axis whereas the speeds (from 0-10 mph) are along ay-axis. Each of the bars 356-5, 356-6 . . . 356-4 along the y-axis showaverage speed for each month. Bars 356 can be colored to conveyinformation, for example, bar showing the month with the highest averagespeed 356-9 of about 9 mph, is a different color (e.g. blue) than thebars for the other months (e.g. green).

At the bottom of the trend report 355, a fleet report 335 e similar tothe fleet reports 335 a, 335 b, 335 c, 335 d in FIG. 3A shows rankedspeeds for the vehicles in the group 357 in the month with the highestaverage speed 356-9 in the graph 358 in a top portion of the userinterface 35. Each vehicle v1, v2 . . . vn is ranked from highest tolowest for that month, with bar graphs for miles per hour for eachvehicle shown along the x-axis and rank from highest to lowest in alongthe y-axis. The display could be configured to allow a user to selectany month for a breakdown.

Within the Ranking List of vehicles shown below the graph, the Industryand/or Geography that a user selects can be added as a ranking graphic380 in the correct ranking position. The system is configured such thatif the Industry and/or Geography ranking graphic 380 (e.g., FieldServices, New York) has a value that is the fourth highest compared tothe vehicles in that fleet, then the ranking graphic 380 should be inthe fourth position of the list and should resemble a driver or dailyaverage as it appears in the list, but distinguished from the otherrankings v1, v2 . . . Vn by a distinguishing indicia, such as being in adifferent color or highlighted. In one embodiment, the color of theranking graphic 380 can match the color in the peer comparison trendinggraphic 376 overlay in the graph. The system can be configured to allowa user to remove the graph from the chart, as for example with a “Removefrom chart” link 374 to the right of the “Graph” button 374 that removesboth the graph as well as the item from the Ranking list.

The trend data can include operational performance against at least onecriterion, the at least one criterion including a criterion selectedfrom at least one of: a user-configurable criterion; a criterion derivedfrom GPS event data; a criterion derived from data other than GPS eventdata; a criterion derived from traffic data; and a criterion derivedfrom industry data. FIG. 3J shows at 390 another example of trend reportand alert based on a trend analysis. As shown, a “Stories” 390 reportshows that in a fleet of vehicles, 202 vehicles had more than 20 highspeed events in a given month, whereas the industry average is 7 permonth. As shown, the alert 390 shows, based on a criterion derived fromthe GPS event data, which shows that the Trending for the operationalmetric is high 391. While such a criterion can be derived from GPS eventdata from the fleet from that user, it can also be derived from non-GPSevent data such as industry standard data derived from, for example GPSdata of other users or external databases that hold data related tooperational statistics.

In the embodiment shown in FIG. 3L a Trending Graph 358 is shownincluding a peer comparison trending graphic 376. The peer comparisongraphic trending 376 can be overlaid on top of the trending graph forthe fleet. In an embodiment, the color used for the overlay matches thecolor used for an “Apply” or “Graph” button 374 within the peercomparison selection, although other graphics or identifiers can be usedto correlate the overlay with the peer comparison selection area.

In one embodiment, the system is configured such that a user can addonly one graph 376 to the chart 358 for peer comparison. The system isconfigured such that when a user selects a different option withineither of the dropdowns 370, 372, the existing graph should be replacedwith one for the new selection.

FIGS. 3L and 3M show examples of a detailed trend report 355 for a fleetand employees from trending analysis as described where the trendingincludes a peer comparison. As shown, a “Trending” page could beaccessed, for example, in a page from the “Dashboard.” In FIG. 3M thetrending 335 is an “Distance Traveled” report 335 for the averagemileage 302 b for at least one fleet group over a time period 364, forexample 3 months, 6 months, a past year, a selectable year (e.g. 2010,2011) or “all” (e.g. a full time period for which data was collected fora given user). It will be noted that the time period available to agiven user depends on how much GPS event data stored for the fleet forthat user. For example, a user whose fleet data is collected startingJan. 1, 2011 would not have options for data before that time.

At the bottom of the trend report 355, a fleet report 335 e shows aranking list 335 e ranked daily average mileages of the fleet 357 in agiven month (April 2011). Each day d1, d2 . . . dn is has bar graphs foraverages for daily distances for the fleet shown along the x-axis. Thedisplay could be configured to allow a user to select any month for abreakdown.

Similar to the description above, within the Ranking List of vehiclesshown below the graph, the Industry and/or Geography that a user selectscan be added as a ranking graphic 380 in the correct ranking position.The system is configured such that if the Industry and/or Geographyranking graphic 380 has a value that is the fourth worst compared to thevehicles in that fleet, then the ranking graphic 380 should be in thefourth position of the list and should resemble a driver or dailyaverage as it appears in the list, but distinguished from the otherrankings d1, d2 . . . dn by a distinguishing indicia, such as being in adifferent color or highlighted. In one embodiment, the color of theranking graphic 380 can match the color in the peer comparison trendinggraphic 376 overlay in the graph. The system can be configured to allowa user to remove the graph from the chart, as for example with a “Removefrom chart” link 374 to the right of the “Graph” button 374 that removesboth the graph as well as the item from the Ranking list.

in one embodiment, an “Average per Day” sub-metric is configured toallow a user to see Trending based on the average per day per vehiclefor whichever metric is selected. As shown in FIG. 3N a sub-metricdropdown includes an “Average per Vehicle” and “Average per Day”options.

In an embodiment, if summarized data is a row for each day for eachvehicle, then the Average per Day value can be found by getting theaverage value for each metric. The system is configured such that if avehicle does not have any vehicle activity for that day, then that dayis not included. If, however, a vehicle does have vehicle activity, butthe value for that particular metric is 0 (e.g. 0 for idling if thedriver did not idle), that 0 value is included.

In an embodiment including an Average Speed metric, the data is the sameas that of “Average per Vehicle” and “Average per Day.” Accordingly, thesystem can be configured to include an “Average per Day” option in thedropdown have the data be the same for both “Average per Day” and“Average per Vehicle.” In an embodiment, the option is not removed fromthe dropdown when “Average Speed”, as that causes the selectedsub-metric to change as the vehicle metric changes.

Described are calculations for the Industry/Geography Segment for thevarious sub-metrics.

In an embodiment, data points are used from both the segment comparisonsthat are being calculated on a periodic basis as well as GPS event databeing transmitted for a given user's fleet.

Segment data points include average per vehicle per day forindustry/geography segment. A given fleet's data points include totalnumber of active unique vehicles for that fleet, and total number ofvehicle days for that fleet (i.e. the number of rows). The averagenumber of days a vehicle from a fleet was active in that month is foundby taking the total number of vehicle days for that fleet divided by thetotal number of active unique vehicles for that fleet.

For the “Average per Day” the average per vehicle per day calculated forthe industry/geography segment that was selected is used. The Averageper Vehicle is calculated by taking the [Average per vehicle per day forselected segment] times [Average number of days a vehicle from thatcustomer was active in that month]

Exemplary benchmark input for the Average Vehicle-Day value is shown atFIG. 8. As shown at FIG. 8, a total is calculated by taking the [Averageper vehicle per day for selected segment] times [Total number of vehicledays for that fleet (i.e. the number of rows)]. As the Average Speedmetric is viewed as the average per vehicle, the Peer Comparison valueis the same for each of the three sub-metrics and it would always showthe average per vehicle.

In another embodiment, the system is configured to allow users to setdefaults and contribute to peer comparisons. As shown in FIGS. 3S and 3Tpages can be created allowing the user to setup a default Industryand/or Geographic Region/Type that will be used as context in otherareas when the user is setting company parameters. For example, in anembodiment a page could be set up which describes peer comparisons andhow they can be used within the application. In an embodiment, the pagecan include a number of buttons, allowing the user to toggle betweenselecting an industry and a Geographic Region/Type. The Industry areacan include a graphic such as a picture or identifier for the commonvehicle type that goes along with each of the different Industries. Forexample, mousing over each industry highlights that industry in yellowand shows a floating box that describes the industry and the SIC codeswithin that industry. For each company parameter that is shown in theapplication, a horizontal scale can be used to control and set thevalue. In one embodiment, a Peer Comparison that that the user choosescan be shown as a vertical tick mark with a label underneath it statingthat is the peer comparison. The page(s) can offer options to opt-in orout to providing GPS data for the industry or region.

Other metrics may be included, such as indications of speeding incidents(severity, violations, thresholds), or fuel related metrics.

In another embodiment, the system is configured to integrate peercomparisons into a fleet's vehicles operational parameters. GPS eventdata such as GPS-based accelerometer data can be collected as the systemis implemented.

For example, in an embodiment a fleet's average idling duration can becompared to peers with using peer metrics as described herein. Thenumber of vehicles that are above and below the peer's idling durationcan also be included. The fleet's average distance traveled can also becompared to peers using peer metrics. The number of vehicles that areabove and below the peer's distance traveled can also be included. Alsothe fleet's average hours worked in a day can also be compared to peersusing peer metrics. The number of vehicles that are above and below thepeer's daily hours worked are included.

The fleet's average idling duration compared to peers using peermetrics. The number of vehicles that are above and below the peer'sidling duration can be included.

The fleet's average distance traveled compared to peers using peermetrics. The number of vehicles that are above and below the peer'sdistance traveled can be included.

The fleet's average hours worked in a day are compared to peers usingpeer metrics. The number of vehicles that are above and below the peer'sdaily hours worked can be included.

FIGS. 3O and 3P show other examples of a detailed trend report 360 for afleet and employees from trending analysis as described above. Thedisplay shows a “head to head” analysis of two drivers v1, v2, each ofwhich can be selected by drop down menus 360 a, 360 b, which can also beconfigured to be searchable. The head to head analysis can be selectedusing a drop down and/or searchable menu 361 for over any over a timeperiod, for example 3 months, 6 months, a past year, a selectable year(e.g. 2009, 2010, 2011) or “all” (e.g. a full time period for which datawas collected for a given user). Again, it will be noted that the timeperiod available to a given user depends on how much GPS event datastored for each driver and/or vehicle. For example, a user whose fleetdata is collected starting Jan. 1, 2011 would not have options for databefore that time. Similarly, data would not be available for a givenvehicle or driver for any time period where data was not collected froma GPS device associated with that user or driver. Once the vehicles v1,v2 and the time period are selected, a user can, via an input 367, runthe comparison. As described below, the trend report can be configuredfor a “head to head” comparison between a driver (or fleet) and a peermetric.

A top section 362 of the page shows a “versus” trend comparison, whichpresents graphics comparing a vehicle's v1 performance against a peerperformance metric P (e.g., an industry segment and/or geographiccomparison) under operational metrics 302 as described herein, forexample: Engine On/Off 302 a, Vehicle Mileage 302 b, Vehicle Idling 302c and Average Speed 302 e. As shown in FIG. 3O, each operational metric302 includes a bar graphic 365, where the left-side 365 v 1 of the barcorresponds to one driver v1 and the right side 366P of the barcorresponds to another the peer metric P. A visual indicia for the bar,for example a color, is given for each the driver and the metric v1, P,which allows a user to readily compare performance trends and statisticsunder each operational metric 302 for driver v1 and the peer P metricfor the time period selected (e.g., 2009). A text graphic 366 v 1 mayalso give statistical trend data. For example, as shown in FIG. 3O,driver v1 has under “Engine-On Time” 302 a, a green color on theleft-side 365 v 1 of the bar that is not as long as the peer performancemetric P red color on the right-hand side of the bar 365P. Text graphics366 v 1, 366P at the left and right hand extremes of the bar showrespectively that driver 1's v1 engine-on time is 5,234 minutes 366 v 1,whereas the peer performance metric's P engine on time is 7,556 minutes366P. In the example shown in FIG. 3P, driver v1 has under “Engine-Time”302 a, a green color on the left-side 365 v 1 of the bar that is againnot as long as the peer performance metric's P red color on theright-hand side of the bar 365 v 2. In FIG. 3P, text graphics 366 v 1,366P at the left and right hand extremes of the bar show respectivelythat driver 1's v1 engine on time for all years is 280,312 minutes 366 v1, whereas the peers' P engine on time for all years is 298,498 minutes366P. The statistics are given in the same layout for Vehicle Mileage302 b, Vehicle Idling 302 c and Average Speed 302 e, thus allowing auser to readily see and compare how the driver v1 and the pees Pperformed for the time period selected (e.g. the year of 2009, “allyears”).

A bottom section 363 of the page shows an XY graph which plots thestatistics for each driver in increments for the “versus” trendcomparison. Page tabs 368 for the graph report 363 allows the user tosee XY graphs 363 for each of the operational metrics Engine On/Off 302a, Mileage 302 b, Vehicle Idling 302 c and Average Speed 302 e. As shownin FIG. 3Q, Mileage 302 b for a year is presented, whereas in FIG. 3P,Engine-On Time 302 b for “all years” is presented. In FIG. 3Q, along theX-axis are increments of months, and along the Y-axis is vehicle mileagein 1000 minute increments. In FIG. 3P, along the X-axis are incrementsof years for “all years”, and along the Y-axis is Engine-On time inminutes per month. The driver v1 and the peer performance metric P has abar graph 364 v1, 364P plotted along the XY axis showing theirperformance over time. A visual indicia for the bar, for example acolor, is given for the driver v1 and the peer P, which allows a user toreadily compare performance trends and statistics for the operationalmetrics 302 for the time period selected, and can be configured tocorrespond to the colors assigned to the driver and the peer performancemetric in the top portion 362 of the report.

Also, one or more trend bar graphs can be added to show a comparison forat least one criterion, for example a criterion selected from: auser-configurable criterion; a criterion derived from GPS event data; acriterion derived from data other than GPS event data; a criterionderived from traffic data; a criterion derived from traffic data; and acriterion derived from industry data. For example as shown in FIGS. 3Oand 3P, a fleet average bar 364avg shows a fleet average performance forthe operational metric 302 selected (e.g., Vehicle Mileage in FIG. 3Q,Engine-On Time in FIGS. 3O-3P). Accordingly, a user can readily see acomparison of a selected driver (or drivers) v1 and a peer metric Pagainst one another (e.g. industry segment), and also as against theselected criterion or criteria such a fleet performance. In anotherembodiment (not shown), the criterion can be drawn from industry data asdescribed herein, and the representation of the trend can be, forexample, graphic presentations such as a bar graph shown showingperformance against an industry benchmark derived from the industry data(e.g. industry averages for operational metrics as described herein,best-of-class industry averages, goals met/unmet vs. industrystandards). For example, a graph could show an average of the toppercent of industry performers for which there is industry data. Thescreen could also show goal benchmarks set by a user, as could bedeveloped from industry data, and whether the vehicles or fleet aremeeting those goals.

As shown in FIG. 3Q and FIG. 3R, any number of vehicles or drivers v1,v2 . . . vn can be added to the graphics to permit comparisons asdescribed above. For example, FIG. 3Q shows a multi-vehicle graphic 365where a user is presented with an XY axis 363 for the operational metricMileage 302 b for the year 2009, similar to those described above withrespect to FIGS. 3Q-3R, which includes an input area 360 a for adding asmany vehicles v1, v2, . . . vn as a user desires, as well as allowingaddition of one or more peer comparisons P1, P2.

As shown in FIG. 3Q, 3 vehicles/drivers v1, v2 and peer comparison P for“All Industries, New York” are compared for the year 2009. In anotherembodiment, the system can be configured to analyze GPS data and othercriteria data (e.g., industry segment data) to allow for intelligentreporting. For example, as shown in FIG. 3Q, a text graphic 369 alsoshows the totals for all vehicles selected, as well as a “Peak Period”which the month with the peak driving mileage (August 2009), as well asthe monthly mile total for the vehicle/driver with the highest mileagethat month (v1 with 8711.62 miles in August 2009). Thus the system thusshows trend data along with, for the drivers selected, the driver whowas the largest cause. The system can be further configured to analyzethe GPS event history for at least one driver's performance for at leastone operational metric, identify a change in performance in at least oneoperational metric over a time period; provide, for the graphic userinterface, the representation of the trend, the trend including a trendshowing the change in performance for the operational metric.

FIG. 3R shows a multi-vehicle comparison graphic 390 where a user ispresented with an XY axis 363 similar to those of FIGS. 3O to 3P andFIG. 3G for the operational metric “Idling” 302 c for the year 2009. Thegraph plots the minutes spent idling for the “top 3” vehicles v1, v2,v3, for the year 2009. Also shown are two peer comparison trendinggraphics, “All Industries, New York” P1 and Field Services, New York”P2. As will be understood, the comparison 390 may show either the leastamount of minutes spent idling, which is a positive performingstatistic, or the “top 3” could be configured to show those in the fleetwith the highest minutes spent idling, which would be a negativeperforming statistic. A text graphic 369 also again shows the totals forthe top 3 vehicles, as well as a “Peak Period” which the month with thepeak idling time (September 2009), as well as the idling minute totalfor the vehicle/driver with the highest idling minutes that month (v3with 11,349 mins. in September 2009). Thus the system thus shows trenddata along with, for the top 3 drivers, the driver who was the largestcause.

in another embodiment, system can be configured to proactively generatereports or alerts based on, inter alia, analyses of GPS event data andnon-GPS event data as described herein. The system can be configured toanalyze the GPS event history for at least one driver's performance forat least one operational metric, identify a change in performance in atleast one operational metric over a time period; provide, for thegraphic user interface, the representation of the trend, the trendincluding a trend showing the change in performance for the operationalmetric. For example, in a current time period where GPS vehicle data isshowing that an operational metric is trending above or below from aprior time period, the system can be configured to report and/or alertthe user. For instance, in a current month where idling is up X % overthe prior month, the system can be configured to deliver an alertshowing the total idling for the present month and thevehicle(s)/driver(s) with the highest idling minutes that month, therebypinpointing a cause. Similar alerts could be configured for anyoperational metric, (average speed, mileage, speeding, etc.) and for anytime period (day, week, month, quarter, year, etc.) Comparisons could berun on other bases as well, for example, a delta for an operationalmetric from another time period (e.g., idling is up or down X % from thesame month of the previous year, or the same week of the previous month,etc.) Such analyses can be performed for a single driver up to an entirefleet.

Criteria developed from GPS event data and non-GPS event data such asindustry data or historical GPS event data can be used to developcriteria to configure such benchmarks. For example, where historical GPSdata and/or industrial data show peak periods for certain operationalmetrics, a higher percentage threshold could be established beforesending an alert than in a non-peak period. The system could also beadapted to incorporate goal benchmarks, and to alert a user when adriver is or is not meeting or exceeding benchmarks.

In another embodiment, the system can be configured to develop criteriausing industry data from industry databases and/or historical GPS eventdata. For example, industrial and/or historical GPS data may show driveror fleet performance metrics and trends for given operational metrics.The system can be configured to facilitate a user in understanding anddeveloping internal goals as against benchmarks developed fromindustrial and/or historical GPS data. For instance, the system could beconfigured to alert the user that it should set up an idling report fora given driver/vehicle, or that a mileage report should be set up forthe fleet, based on the trending data from past performance.

In another example, the system could be configured to allow the user toset monthly fleet goals for a plurality of operational metrics. Insetting each goal, the system could send a facilitating message,alerting the user as to how the goal compared against a criterion suchas an industry benchmark from industrial data and/or a benchmark basedon historical GPS event data. For example, a user enters a goal for thefleet in a goal entry field (not shown) of keeping average minutes pervehicle for idling in a peak month to 5000 miles. The system can beconfigured to access historical GPS data and industry data to comparethat goal against industry benchmarks and send a facilitating message,such as: “Only X % of fleets keep average idling per vehicle under 5000miles.” Analysis of fleets and vehicles for that use can be filtered byany number of factors to target the goal-setting benchmarks, forexample, by geographical region or other relevant filtering data. (e.g.state, city, zip code, service area, comparable cities), fleet size,types of vehicles (truck, car, vehicle class), operational period (year,month), type of business (food delivery, furnishings delivery, packagedelivery), and so on. The system can further be configured to allow suchgoal settings for fleet subsets or selected drivers.

As will be understood, as more GPS data events are accumulated, accuracyand options for reporting can become mote robust as well.

As explained above, any of the presentations above could be configuredsuch that criteria trend graphics can be added to show a comparison forat least one criterion as described herein (e.g.: a user-configurablecriterion; a criterion derived from GPS event data; a criterion derivedfrom data other than GPS event data; a criterion derived from trafficdata; a criterion derived from traffic data; and a criterion derivedfrom industry data).

In one embodiment, the computer system is configured to identify a trendfor at least one operational metric for a first period; provide acriterion for the operational metric; identify a trend for the at leastone operational metric for a second period; compare the trend for thefirst period against the second period to identify a change ofperformance for the trend; and determine if the change of performancefor the trend meets the criterion. For instance, a user could identify atrend of high idling (e.g. up 7%) for a given month, and set a criterionfor idling. For example, the user may input a benchmark of reducingidling by 5%. The system could then analyze GPS data to identify theidling trend for the following month, and determine if the fleet idlingis or is not meeting the 5% reduction. As will be understood, the datacan be provided over any selected time period(s), per driver/vehicle, aselect set of drivers, fleetwide, and for any operational metric, and soon.

FIG. 4 shows a flow chart for a method of presenting GPS event data fora graphic user interface, including in accord with embodiments asdescribed herein. As shown in block 402, the system receives GPS eventdata transmitted from a plurality of GPS devices, each GPS deviceassociated a vehicle. At block 404, the system stores, for each vehicle,in a memory operatively coupled to at least one of the processors theGPS event data over an operation period. At block 406, the GPS eventdata is analyzed to derive a plurality of operational metrics for eachvehicle. At block 410, the system provides, for a graphic userinterface, an interactive display configured display a representation ofat least one operational metric for each of a plurality of vehicles.

In one embodiment the system is can be configured to correct GPS eventdata to provide accurate tracking data for a vehicle. The systemcorrects, using at least one correction algorithm, GPS event data from avehicle. At least one correction algorithm, when executed comprisesidentifying at least one GPS location event for a vehicle 407, and thenas shown at step 408 determines if the event is accurate for thevehicle. In one example, up to date mapping may place the vehicle in animpossible or inaccessible location, such as on the top of a building orin the middle of a body of water with no nearby bridge or road. In sucha case, the event is determined to be inaccurate, and the event data iscorrected, for example, by excluding it from the tracking and reportingdata, or by recalculating a trajectory from a prior position. In anotherexample, a plurality GPS location events for a vehicle can beidentified, where, upon comparing at least one of the plurality GPSlocation events with a different one of the plurality GPS locationevents, it can be determined that at least one of the location events isinaccurate for the vehicle. For example, a GPS signal may indicate tothe system that a vehicle distance from a prior position is too far(e.g., a 5 mile radius) from its prior position as reported 60 secondsprior and when accounting for the maximum possible speed for thevehicle, or some other criterion. Or, in another example, a series ofGPS signals may shown for events that the next signal, if in the next 60seconds, must be in a range (e.g., a 0-3.5 mile radius from the priorpoint), and if the signal is not in that range, the GPS event is false.In such a case, the event data is corrected, for example, by excludingit from the tracking and reporting data, or using some other correctionrecalculation.

Systems and modules described herein may comprise software, firmware,hardware, or any combination(s) of software, firmware, or hardwaresuitable for the purposes described herein. Software and other modulesmay reside on servers, workstations, personal computers, computerizedtablets, PDAs, and other devices suitable for the purposes describedherein. Software and other modules may be accessible via local memory,via a network, via a browser or other application in an ASP context, orvia other means suitable for the purposes described herein. Datastructures described herein may comprise computer files, variables,programming arrays, programming structures, or any electronicinformation storage schemes or methods, or any combinations thereof,suitable for the purposes described herein. User interface elementsdescribed herein may comprise elements from graphical user interfaces,command line interfaces, and other interfaces suitable for the purposesdescribed herein. Except to the extent necessary or inherent in theprocesses themselves, no particular order to steps or stages of methodsor processes described in this disclosure, including the Figures, isimplied. In many cases the order of process steps may be varied, andvarious illustrative steps may be combined, altered, or omitted, withoutchanging the purpose, effect or import of the methods described.

The system can also be configured to provide mapping and trackingfunctions, as described above. The system can be configured to interfacewith mapping systems, for example, such as Google Maps(http://maps.google.com/maps), www.mapquest.com, www.mapsonus.com,www.maps.expedia.com, www.maps.yahoo.com (accessed throughwww.yahoo.com), www.maps.com, www.maps.excite.com, (accessed throughwww.excite.com), and www.mapblast.com. Also see U.S. Pat. Nos.4,974,170, 5,682,525 and 6,148,260, the entirety of each of which isincorporated by reference herein. The system can also be integrated withsystems to able to get real-time traffic information via the mapping inorder to help drivers avoid traffic congestion.

In one embodiment, the system is configured to receive GPS event datafor at least one vehicle; derive speed and location data from the GPSevent data; analyze the GPS event history database for the vehicle'shistorical GPS event data; compare the GPS event data and the eventhistory against traffic data from a traffic database; identify a trafficcondition for the location; and remodel at least one solution tooptimize performance based on the traffic condition and the GPS eventdata. Remodeling the solution can include at least one of a time shiftand rerouting the vehicle. For example, the system can receive GPS eventdata from a vehicle/driver, which sends location and speed informationfor that vehicle. For example, GPS event data signals that a vehicle Vis moving slowly or stopped on Route 20 in Anytown, USA at 9:15 am. Thesystem then accesses traffic data for Anytown, USA and GPS historicaldata for vehicle V against which to compare the GPS event data. Trafficdata can show, for example the times at which the Route 20 is congested(7:30am-9:30am on weekdays), and the GPS historical data can show thetimes at which that driver starts and ends its daily operations (e.g.,7:30am on Tuesdays). The system can then remodel a solution which allowsthe vehicle to avoid the traffic condition. For example, the system mayindicate that if the vehicle V starts its weekday run at least 30minutes later, it will avoid the congestion on Route 20. Or the systemmay reroute the vehicle along route that data analysis shows is lesscongested. The system can also be configured to combine such solutions(e.g., configure a route with a number of route changes and that starts20 minutes later to avoid a number of congested areas, including Route20). The system could be further configured to provide such roadprofiling and route profiling in the form of alerts and reports asdescribed herein. For example, the system could, upon receiving GPSevent data signaling that a vehicle V is moving slowly or stopped onRoute 20 in Anytown, USA at 9:15am, send an alert based on the analysissuch as: “Vehicle 1 should start its Tuesday shift 30 minutes later(8:00am).”

In another example, the system is configured to analyze GPS event dataand data from external databases to provide reports or alerts for driverbehavior or vehicle behavior. For instance, a database can show thetypes of fuel a driver purchases (e.g. from a credit card) and where andwhen a driver refuels. For example, the GPS data and fueling data mayshow that a driver of a vehicle V, “Steve,” fills up with 20 Gallons onTuesdays and Thursdays at “Ritz Gas” on Park Avenue, Anytown, USA.External databases on gas prices show that this station is particularlyhigh priced, and moreso still on Tuesdays and Thursdays. The systemcould be configured to send an alert or give a report indicating thatSteve is paying more for gas than needed. The system could also beadapted to model a solution to avoid the higher priced gas. For example,the system may indicate that if Steve refuels on Monday and Wednesdaysat Acme Gas, on Poverty Lane, Anywhere USA, Steve will pay less for gas.

The system can also be configured to send an alert if the GPS event dataand data from external databases indicates an inconstancy. For example,where Steve fills up with 20 Gallons on Tuesdays and Thursdays, the GPSdata combined with data about the vehicle type and fuel data may showthat Steve's gas consumption is greater than the vehicle's capacity,indicating that Steve purchasing more gas (i.e. for another car) than heis using.

In another embodiment, the system can be configured to store a record ofa route from an origin location to a destination location and record theroute for provision to a computer configured to display the route as amap. A mapping integration including functionality to replay traveledroutes such as a “Route Replay” function is described in U.S. patentapplication Ser. No. 13/083,222 entitled “System and Method forProviding an Electronic Representation of a Route,” the entirety ofwhich is incorporated by reference hereby.

FIG. 1D shows one embodiment of a computer system 10 is configured toprovide an electronic representation of a route. The system isprogrammed to store in a memory operatively coupled to at leastprocessor, a record of a route from an origin location to a destinationlocation. A client computer 184, 194 may be configured, for example, tohave software programmed to store a record of a route locally, or theclient may access a server 204 of a service provider that stores andmaintains records of such routes in a DBMS 208.

The system 100 is configured to provide a user with a plurality ofground level area representations of locations corresponding locationsalong the recorded route including an origin location and a destinationlocation. A description of exemplary embodiments of systems and methodsfor generating and providing ground level area representations can befound at in U.S. patent application Ser. No. 12/391,516, the entirety ofwhich is incorporated by reference herein.

In one embodiment, a map database 270 of server 204 stores map-relatedinformation 272, 274, 276 at least a portion of which may be transmittedto a client device 184,194. As shown in FIG. 1D, for example, mapdatabase 270 may store map tiles 272, where each tile is a map image ofa particular geographic area. Depending on the resolution (e.g., whetherthe map is zoomed in or out), one tile may cover an entire region suchas a state in relatively little detail. Another tile may cover just afew streets in high detail. The map information is not limited to anyparticular format. For example, the images may comprise street maps,satellite images, or a combination of these, and may be stored asvectors (particularly with respect to street maps) or bitmaps(particularly with respect to satellite images). The various map tilesare each associated with geographical locations, such that the server204 is capable of selecting, retrieving and transmitting one or moretiles in response to receipt of a geographical location.

As noted below, the locations may be expressed in various ways includingbut not limited to latitude/longitude positions, street addresses,points on a map (such as when a user clicks on a map), building names,other data capable of identifying one or more geographic locations, andranges of the foregoing.

The map database may also store ground level images 274 such as “streetlevel” images. Ground level images 274 comprise images of objects atgeographic locations, captured by cameras at geographic locations, in adirection generally parallel to the ground. Thus, as shown in FIG. 9A,ground level image data may represent various geographic objects such asbuildings 722, sidewalks 730 and street or road 740 from a perspectiveof a few feet above the ground and looking down the street or road. Itwill be understood that while ground level image 720 only shows a fewobjects for ease of explanation, a typical street level image willcontain as many objects associable with geographic locations (streetlights, mountains, trees, bodies of water, vehicles, people, etc.) in asmuch detail as the camera was able to capture.

The ground level image 720 may be captured by a camera mounted on top ofa vehicle, from a camera angle pointing roughly parallel to the groundand from a camera position at or below the legal limit for vehicleheights (e.g., 7-14 feet). Ground level images are not limited to anyparticular height above the ground, for example, a street level imagemay be taken from the top of building. Panoramic street-level images upto 360 degrees may be created by stitching together a plurality ofphotographs taken from different camera angles.

The system 140 is configured cause the display device 155 to displaythereon a plurality of sequential displays of the ground level arearepresentations 720 for locations along a route, as shown in FIGS. 9-10.In one embodiment the route includes a first display comprising anorigin location area representation; a plurality of sequential displayscomprising sequential location area representations along the route; anda last display of a destination location area representation. The system140 can be configured to receive at least one ground level imagerepresentation for each location along the route, or for selectedlocations along the route.

In one embodiment, the system is programmed work in conjunction with asystem configured to provide a record of a route recorded by a GPS(Global Positioning System) device, for example, using an on-board unitwhich uses technology such as GPS to monitor a vehicle's positions andtransmit wireless uploads to a central host system, as described herein.

One or more systems 100 can be further programmed record the route. Therecorded route can then be provided to a computer system 100 configuredto display the route as a map on a display device 151 of a client device184, as described above. The computer system 100 can then be configuredcause the display to display thereon the plurality of sequentialdisplays of the ground level area representations along the recordedroute so as to replicate a first person view of the route. The system140 is configured to provide to the graphic user interface 151 auser-interactive interface to control and replay the ground levelsequential displays as shown in FIG. 10.

For example in one embodiment, an on-board GPS unit uploads one or morepoint-to-point routes it as traveled to a central host system. Thesetraveled routes can be presented to a user on a display device 151, forexample, as a layout shown in FIGS. 9A-9C. At 700, the routes taken forat least one vehicle can be displayed in an interactive graphic. Asshown in 700, one screen has a scrollable interface for viewingstatistics and routes taken for a vehicle for a number of days 702 a,702 b, 702 c . . . 702 n. As an alternative, routes taken for each of afleet of vehicles on a given day could be presented. For example asshown in FIG. 9C, a “Live Fleet” 324 shows GPS data and mapping softwarewhich tracks vehicles v1, v2 . . . vn. Each day or vehicle can have, forexample, statistics for one or more routes R1, R2, R3, R4 . . . Rnrecorded for that vehicle by an on board GPS device, as well as a totalRT. The origin and destination for route can be determined in any numberof ways, as for example between deliveries for a delivery service (e.g.,the origin being the start of day, the destination being the firstdelivery point, which thereafter is the origin point for the nextdelivery destination, and so on until the end of a work period forvehicle operation, for example, an workday). In another example, anorigin point can be the point where the vehicle's work period starts andthe destination where it ends (e.g. end of vehicle operation for a givenworkday). The definition of a route for a vehicle can thus be defined interms of the needs of a given business or other measurement model.

Locations and time stamps can also be provided for points along theroute (e.g., every 60 seconds) in a graphic 703, where speeds 616 can begiven. Speeds can be rounded up or down in accord with a rule (nodecimal point), or can be more exact (with decimal point. For example, arounding rule can be applied such than above 5 mph or kmph gets roundedup and anything below gets rounded down.

In embodiments including a speed database comprising speed data such asposted speeds or average road or traffic speeds, if a vehicle exceeds aposted speed limit for allocation, then it will be flagged in thejourney graphic 703. Similar to the exceptions En in the “Red Flag”report 600, the posted speed limit E can be displayed in icon form E andthe speed 606 can be displayed in red. For example, for each exceptionE1 the driver's mph at the location 616 is in red and an icon, a redcircle with the number “60,” indicated that the posted speed for thatlocation is 60 mph. A “mouse-over” can also display text with furtherdetails when a pointer is placed on an exception. If the user is in“street view” of ground level images as described herein, the postedspeed can be displayed in a bottom right corner graphic 701 and theexcessive speed displayed in red. The mouse-over can also be configuredto work on a Multi Route Replay as shown at 702 a and 702 b and in FIG.9C when a position information (arrow) icon is clicked. Also similar tothe other speed reports and alerts for a vehicle, (e.g. the Red FlagReport 600) if the “posted speed” feature is not switched on then thespeed threshold warnings for reporting and alerting for, among otherthings, speeds in excess of speed thresholds 70 mph 306 d, 80 mph 308 d,and 90 mph 309 d, with different colors for each (e.g. green, yellow,and red as shown in a driver's speed graphic 610 herein) can show in thejourney graphic 703 as well as, if implemented, on the bottom rightgraphic 701 of the ground level image.

For each route, a number of points representing locations along theroute can be recorded from the GPS and stored at the DBMS 208 of acentral host system. A displayable map can be offered as described aboveand as shown in 710. As shown at 710, the four routes are overlaid eachwith a distinguishing graphic on a displayable electronic map 710. Inone embodiment, a user can select a recorded GPS route R1 for Vehicle 1using an input device 149 such as a mouse, which would then highlight ordisplay the route R1 on the map 710. For the selected Route R1, the useris presented with a “Route Replay” 720 to give the client a first personperspective of the route.

The system 140 is configured to provide to the graphic user interface151 a user-interactive interface to control and replay the ground levelsequential displays for locations along the route R1. In one embodiment,an input control graphic 722 has user-selectable objects, selectable bya mouse or key inputs for example, has at least one fast forward object724 at least one play/pause object 723,725 and at least one rewindobjects 727. A user can select these objects to start, stop, and controlthe speed of a first person view of a sequence T1, T2, T3, T4, T5 ofground level images such as street view photographs along the route R1recorded by the GPS, as shown in FIG. 8. An icon 712 could also beprovided on the map 710 or in another area of the graphic which movesalong with the sequence of images presented in the “Route Replay.” Agraphic 703 can also show locations and time stamps can also be providedfor points along the route (e.g., every 60 seconds).

FIG. 10 shows a time sequence T1, T2, T3, T4, T5 . . . Tn of groundlevel images 720 that are presented to a user on a display device 151.As shown in FIG. 10, in one embodiment, the sequence, T1, T2, T3, T4, T5. . . Tn of ground level images is played for locations along the routein a manner like a slide show, giving the viewer a first person view ofthe exact route taken by the vehicle on a time-scale proportionate tothe vehicle's movement. Thus in such an embodiment, the speed, startsand stops of the vehicle will be presented so as to reflect the recordedroute as traveled vehicle.

In another embodiment, a preset play speed causes the display device 151to display thereon the plurality of sequential displays in a timesequence different than that of the speed and movement of the vehiclerecorded by the GPS. Thus, for example, the sequence of ground levelimages such as photographs of points along the route, may be presentedslower than a “real time” record of the route to allow for a moreviewer-friendly presentation of the sequence of images where, forinstance, a real time presentation would present the images in sequencetoo quickly.

In another embodiment, transitioning from image to image may be smoothedor made more continuous, as described in incorporated reference U.S.patent application Ser. No. 12/391,596. In such an embodiment a “realtime” presentation of a “Route Replay” can be contemplated.

As explained above, panoramic street-level images up to 360 degrees maybe created by stitching together a plurality of photographs taken fromdifferent camera angles. In another embodiment, system 140 can provide,for at least one of the plurality of locations along the route, aplurality of ground level area representations configured to display a360 degree view of the location for the first person view.

Accordingly, while the invention has been described and illustrated inconnection with preferred embodiments, many variations and modificationsas will be evident to those skilled in this art may be made withoutdeparting from the scope of the invention, and the invention is thus notto be limited to the precise details of methodology or construction setforth above, as such variations and modification are intended to beincluded within the scope of the invention. Therefore, the scope of theappended claims should not be limited to the description andillustrations of the embodiments contained herein.

The invention claimed is:
 1. A computer system including at least onecomputer processor and computer readable storage medium or media and atleast one storage device in which is stored GPS data for a plurality ofvehicles, the system comprising: a memory including GPS event databaseincluding GPS event data transmitted from a plurality of GPS devices,each GPS device associated with a vehicle, and stored over a period oftime; and one or more processors programmed at least to receive GPSevent data transmitted from a plurality of GPS devices, each GPS deviceassociated a vehicle; store in a memory operatively coupled to at leastone of the processors, the GPS event data; analyze the GPS event data toderive a plurality of operational metrics for each vehicle; provide, fora graphic user interface, an interactive display configured to display agraphic representation of at least one operational metric for each of aplurality of vehicles, including a representation of a speed limitevent, wherein the system is operatively connected to at least one speeddatabase including speed data, and wherein the at least one speeddatabase including speed data comprises a record of a posted speed limitfor a route and a record of an average road speed for a route.
 2. Thecomputer system of claim 1, wherein the one or more processors arefurther programmed at least to: provide, for the graphic user interface,a graphic presentation of the at least one operational metric, whereinthe operational metric is selected from the group consisting essentiallyof: engine on/off, vehicle mileage, idling, number of stops, speed,performance against a criterion, employee performance; driver behavior;and fleet performance, speeding severity, a speeding violation, averagevehicle speed, a posted speed limit, a speed threshold, and an averageroad speed.
 3. The computer system of claim 1, wherein the one or moreprocessors are further programmed at least to: provide, for the graphicuser interface, an alert when an operational metric for a vehicle meetsor exceeds at least one predetermined criterion established for theoperational metric, wherein the operational metric includes a speedmetric.
 4. The computer system of claim 3, wherein the one or moreprocessors are further programmed at least to: wherein the speed metricincludes at least one of average vehicle speed, speeding severity,speeding violation, a posted speed limit, a speed threshold, and averageroad speed.
 5. The computer system of claim 1, wherein the one or moreprocessors are further programmed at least to store, in a memoryoperatively coupled to at least one of the processors, a record of aroute from an origin location to a destination location; and record theroute for provision to a computer configured to display the route as amap.
 6. The computer system of claim 1, wherein the one or moreprocessors are further programmed at least to: for each vehicle, storein the memory operatively coupled to at least one of the processors,historical GPS event data for a plurality of operation periods.
 7. Thecomputer system of cairn 6, wherein the one or more processors arefurther programmed at least to: generate a report based on saidhistorical GPS event data.
 8. The computer system of claim 7, whereinthe one or more processors are further programmed at least to: generateat least one report based on said historical GPS event data, the atleast one report comprising information including at least one of:vehicle activity over a predetermined time period; a speed report; anidling report; vehicle operational reports; employee performance; driverbehavior; a speed limit report; and fleet performance.
 9. The computersystem of claim 6, wherein the one or more processors are furtherprogrammed at least to: identify, from the analysis, at least one trendfor a GPS event history using the GPS event data; and provide, for agraphic user interface, a representation including a representation ofthe at least one trend.
 10. The computer system of claim 9, wherein theone or more processors are further programmed at least to: identify atrend for an operational metric, wherein the operational metric isselected from the group consisting essentially of: engine on/off,vehicle mileage, idling, number of stops, speed, performance against acriterion, employee performance; driver behavior; and fleet performance,a posted speed limit, speed threshold, and an average speed for a road.11. The computer system of claim 10, wherein the trend includingoperational performance against at least one criterion, the at least onecriterion including a criterion selected from at least one of: auser-configurable criterion; a criterion derived from GPS event data; acriterion derived from data other than GPS event data; a criterionderived from traffic data; a criterion derived from fueling data; acriterion derived from industry data; and a criterion derived from speedlimit data.
 12. The computer system of claim 11, wherein the one or moreprocessors are further programmed at least to: compare the GPS eventhistory for at least one vehicle using the GPS event data against speedlimit data; and provide, for a graphic user interface, a graphicrepresentation of the trend, the trend including a trend showingperformance against a benchmark derived from the speed limit data. 13.The computer system of claim 11, wherein the one or more processors arefurther programmed at least to: analyze the GPS event history for aplurality drivers' performance for at least one operational metric; andprovide, for the graphic user interface, a representation of the trendsfor each of the drivers' performance.
 14. The computer system of claim1, wherein the one or more processors are further programmed at leastto: receive GPS event data for at least one vehicle; derive speed andlocation data from the GPS event data; send an alert if the derivedspeed exceeds a speed limit criterion for the vehicle's location. 15.The computer system of claim 1, wherein the one or more processors arefurther programmed at least to: provide, for the graphic user interface,an alert when an operational metric for a vehicle meets or exceeds atleast one predetermined criterion established for the operationalmetric.
 16. A method comprising, in at least one computer comprising aprocessor and a computer readable storage medium or media: receiving GPSevent data transmitted from a plurality of GPS devices, each GPS deviceassociated a vehicle; storing, for each vehicle, in a memory operativelycoupled to at least one of the processors, the GPS event data; analyzingthe GPS event data to derive a plurality of operational metrics for eachvehicle; and providing, for a graphic user interface, an interactivedisplay configured to display a graphic presentation of at least oneoperational metric for each of a plurality of vehicles, including arepresentation of a speed limit event, wherein the system is operativelyconnected to at least one speed database including speed data, andwherein the at least one speed database including speed data comprises arecord of a posted speed limit for a route and a record of an averageroad speed for a route.
 17. The method of claim 16, wherein the methodfurther comprises: providing, for the graphic user interface, thegraphic presentation of the at least one operational metric, wherein theoperational metric is selected from the group consisting essentially of:engine on/off, vehicle mileage, idling, number of stops, speed,performance against a criterion, employee performance; driver behavior;and fleet performance, speeding severity, a speeding violation, averagevehicle speed, a posted speed limit, a speed threshold, and an averageroad speed.
 18. The method of claim 16, wherein the method furthercomprises: providing, for the graphic user interface, an alert when anoperational metric for a vehicle meets or exceeds at least onepredetermined criterion established for the operational metric, whereinthe operational metric includes a speed metric.
 19. The method of claim18, wherein the speed metric includes at least one of average vehiclespeed, speeding severity, speeding violation, a posted speed limit, aspeed threshold, and average road speed.
 20. The method of claim 16,wherein the method farther comprises: storing, in a memory operativelycoupled to at least one of the processors, a record of a route from anorigin location to a destination location; and recording the route forprovision to a computer configured to display the route as a map. 21.The method of claim 16, wherein the method further comprises: for eachvehicle, storing in a memory operatively coupled to at least one of theprocessors, historical GPS event data for a plurality of operationperiods.
 22. The method of claim 21, wherein the method furthercomprises: generating a report based on said GPS historical event data.23. The method of claim 22, wherein the method further comprises:generating at least one report based on said historical GPS event data,the at least one report comprising information including at least oneof: vehicle activity over a predetermined time period; a speed report;an idling report; vehicle operational reports; employee performance;driver behavior; a speed limit report; and fleet performance.
 24. Themethod of claim 21, wherein the method further comprises: identifying,from the analysis, at least one trend for a GPS event history using theGPS event data; and providing, for a graphic user interface, arepresentation including a representation of the at least one trend. 25.The method of claim 24, wherein the method further comprises:identifying a trend for an operational metric, the operational metric isselected from the group consisting essentially of: engine on/off,vehicle mileage, idling, number of stops, speed, performance against acriterion, employee performance; driver behavior; and fleet performance,a posted speed limit, speed threshold, and an average speed for a road.26. The method of claim 25, wherein the method further comprises: thetrend including operational performance against at least one criterion,the at least one criterion including a criterion selected from at leastone of: a user-configurable criterion; a criterion derived from GPSevent data; a criterion derived from data other than GPS event data; acriterion derived from traffic data; a criterion derived from trafficdata; a criterion derived from fueling data; a criterion derived fromindustry data; and a criterion derived from speed limit data.
 27. Themethod of claim 26, wherein the method further comprises: comparing theGPS event history for at least one vehicle using the GPS event dataagainst speed limit data; and providing, for a graphic user interface, agraphic representation of the trend, the trend including a trend showingperformance against a benchmark derived from the speed limit data. 28.The method of claim 16, wherein the method further comprises: analyzingthe GPS event history for a plurality drivers' performance for at leastone operational metric; and providing, for the graphic user interface, arepresentation of the trends fur each of the drivers' performance. 29.The method of claim 16, wherein the method further comprises: receivingGPS event data for at least one vehicle; deriving speed and locationdata from the GPS event data; and sending an alert if the derived speedexceeds a speed limit criterion for the vehicle's location.
 30. Themethod of claim 16, wherein the method further comprises: providing, forthe graphic user interface, an alert when an operational metric for avehicle meets or exceeds at least one predetermined criterionestablished for the operational metric.